Brain stroke detection from CT scans via 3D Convolutional Neural Network
A tutorial on how to train a 3D Convolutional Neural Network (3D CNN) to detect the presence of brain stroke from Computer Tomography (CT) scans.
Image credit: Giovanni PecoraroIntroduction
The Brain Stroke CT Image Dataset from Kaggle provides normal and stroke brain Computer Tomography (CT) scans. The dataset presents very low activity even though it has been uploaded more than 2 years ago. It may be probably due to its quite low usability (3.13). The challenge is to get some interesting result, i.e., to try to perform brain stroke detection, even from this low-quality CT scans dataset. The followed approach is based on the usage of a 3D Convolutional Neural Network (CNN) in place of a standard 2D one. 2D CNNs are commonly used to process both grayscale (1 channel) and RGB images (3 channels), while a 3D CNN represents the 3D equivalent since it takes as input a 3D volume or a sequence of 2D frames, e.g. slices in a CT scan. The provided example takes inspiration from the great work 3D image classification from CT scans done by Hasib Zunair who clearly demonstrated how to use a 3D CNN to predict the presence of viral pneumonia from CT scans.
Dataset exploration
The CT scans dataset is public available on Kaggle, but for the sake of simplicy it has been made available together with the present notebook on my GitHub so it can be easily downloaded without the need of an API key and additional Python packages.
import os
import zipfile
import tensorflow as tf
# Download dataset from GitHub
url = "https://github.com/Peco602/brain-stroke-detection-3d-cnn/releases/download/v0.0.1/brain_ct_data.zip"
filename = os.path.join(os.getcwd(), "brain_ct_data.zip")
tf.keras.utils.get_file(filename, url)
# Unzip dataset
with zipfile.ZipFile("brain_ct_data.zip", "r") as z_fp:
z_fp.extractall(".")
Downloading data from https://github.com/Peco602/brain-stroke-detection-3d-cnn/releases/download/v0.0.1/brain_ct_data.zip
63160014/63160014 [==============================] - 1s 0us/step
!ls -al brain_ct_data
total 92
drwxr-xr-x 4 root root 4096 Apr 21 07:03 .
drwxr-xr-x 1 root root 4096 Apr 21 07:03 ..
drwxr-xr-x 2 root root 49152 Apr 21 07:03 Normal
drwxr-xr-x 2 root root 32768 Apr 21 07:03 Stroke
The dataset contains both normal and stroke images respectively in the Normal and Stroke folders.
!ls brain_ct_data/Normal | head
100 (10).jpg
100 (11).jpg
100 (12).jpg
100 (13).jpg
100 (14).jpg
100 (15).jpg
100 (16).jpg
100 (17).jpg
100 (18).jpg
100 (19).jpg
!ls brain_ct_data/Stroke | head
58 (10).jpg
58 (11).jpg
58 (12).jpg
58 (13).jpg
58 (15).jpg
58 (17).jpg
58 (18).jpg
58 (19).jpg
58 (1).jpg
58 (20).jpg
It is important to clarify the dataset does not contain CT scans, which are usually provided as DICOM or NIfTI files, but the CT scan slices in JPEG format (most probably extracted from DICOM or NIfTI files). A previous post clearly explains how to extract slice images from a DICOM file. Giving a further look to the slice images it is easy to understand the naming convention PATIENT_ID (SLICE_ID).jpg, e.g. 49 (1).jpg, 49 (2).jpg and for each patient ID several slices are available. The following function is able to plot up to 40 slices (if available) for a specific patient ID.
import matplotlib.pyplot as plt
import imageio.v2 as imageio
import numpy as np
def plot_scan_from_path(slices_path, patient_id):
"""Plot 40 slices for a patient ID"""
num_rows = 4
num_columns = 10
factor = 1.2
f, axarr = plt.subplots(
num_rows,
num_columns,
figsize=(num_columns*factor, num_rows*factor),
)
f.suptitle(f"Patient {patient_id}", y=1.1)
image_id = 1
for i in range(num_rows):
for j in range(num_columns):
try:
img = imageio.imread(f'{slices_path}/{patient_id} ({image_id}).jpg')
except Exception as e:
print(e)
img = np.zeros((2,2))
finally:
axarr[i, j].imshow(img, cmap='gray')
axarr[i, j].axis('off')
image_id += 1
plt.subplots_adjust(wspace=0, hspace=0, left=0, right=1, bottom=0, top=1)
plt.show()
Let’s start with patient 49:
plot_scan_from_path(slices_path='brain_ct_data/Normal', patient_id=49)
No such file: '/content/brain_ct_data/Normal/49 (34).jpg'
No such file: '/content/brain_ct_data/Normal/49 (35).jpg'
No such file: '/content/brain_ct_data/Normal/49 (36).jpg'
No such file: '/content/brain_ct_data/Normal/49 (37).jpg'
No such file: '/content/brain_ct_data/Normal/49 (38).jpg'
No such file: '/content/brain_ct_data/Normal/49 (39).jpg'
No such file: '/content/brain_ct_data/Normal/49 (40).jpg'
Patient 49 has 33 slices, but it is fundamental to underline the slices are not correctly sorted. It seems the slices go from the middle of the head to the top, but then they suddenly start back from the bottom. This may be among the reasons the dataset usability is low. This may not be an issue for a 2D CNN since it takes single images as input, but is a big obstacle for a 3D CNN where the volumetric representation of the brain is needed.
plot_scan_from_path(slices_path='brain_ct_data/Normal', patient_id=50)
No such file: '/content/brain_ct_data/Normal/50 (13).jpg'
No such file: '/content/brain_ct_data/Normal/50 (15).jpg'
No such file: '/content/brain_ct_data/Normal/50 (17).jpg'
No such file: '/content/brain_ct_data/Normal/50 (19).jpg'
No such file: '/content/brain_ct_data/Normal/50 (21).jpg'
No such file: '/content/brain_ct_data/Normal/50 (23).jpg'
No such file: '/content/brain_ct_data/Normal/50 (25).jpg'
No such file: '/content/brain_ct_data/Normal/50 (27).jpg'
No such file: '/content/brain_ct_data/Normal/50 (29).jpg'
No such file: '/content/brain_ct_data/Normal/50 (31).jpg'
No such file: '/content/brain_ct_data/Normal/50 (33).jpg'
No such file: '/content/brain_ct_data/Normal/50 (35).jpg'
No such file: '/content/brain_ct_data/Normal/50 (39).jpg'
No such file: '/content/brain_ct_data/Normal/50 (40).jpg'
For patient 50 the situation is even worse: there are holes in slice sequence, which makes dataset importing even more difficult.
Dataset fixing
Before going deeper into modeling it is necessary to try to fix the dataset otherwise it is quite difficult to expect good results. If you are not interested in this section you can skip it and directly jump to the next one since the fixed dataset is also already available on my GitHub.
The fixing consists of correctly sorting the slices and removing the existing holes. The idea is to create a dictionary where each key represents a patient ID, while the value is the list of correctly sorted images. The creation of such a dictionary was quite demanding since it required to visually analyze the entire dataset to try to determine the correct sequence for each patient.
INPUT_PATH='brain_ct_data'
OUTPUT_PATH='brain_ct_data_fixed'
NORMAL_INPUT_PATH=f'{INPUT_PATH}/Normal'
NORMAL_OUTPUT_PATH=f'{OUTPUT_PATH}/Normal'
STROKE_INPUT_PATH=f'{INPUT_PATH}/Stroke'
STROKE_OUTPUT_PATH=f'{OUTPUT_PATH}/Stroke'
NORMAL_SORTING_CONFIG = {
49: [14, 15, 16, 11, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13],
50: [36, 37, 38, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34],
51: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50],
52: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
53: [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 28, 29, 31, 33, 35, 37, 39, 41, 43, 1, 2, 3, 4],
54: [20, 21, 22, 23, 24, 25, 26, 27, 28, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
55: [30, 31, 32, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
56: [33, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32],
57: [32, 33, 34, 35, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31],
59: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27],
60: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
61: [25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24],
62: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23],
63: [33, 34, 35, 36, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32],
64: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26],
65: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
95: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
96: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33],
98: [29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
99: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
100: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
101: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31],
102: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31],
103: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35],
104: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
105: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
106: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
107: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
108: [25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24],
109: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
110: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
111: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33],
112: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26],
113: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
114: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
115: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32],
116: [31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
117: [29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
118: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
119: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31],
120: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
121: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
122: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
123: [39, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38],
124: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
125: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40],
126: [30, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
127: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32],
128: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28],
129: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
130: [26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25],
}
STROKE_SORTING_CONFIG = {
58: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36],
66: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 38, 39, 40, 41],
67: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 23, 25, 27, 28, 29, 30, 31, 32, 33],
68: [1, 2, 3, 4, 5, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36],
69: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36],
70: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 42, 43, 44, 45, 46, 47, 48],
71: [48, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46],
72: [31, 32, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
73: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 30, 32, 34, 36, 38, 39],
74: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 18, 20, 22, 23, 25, 27, 29, 31, 33, 35, 37, 39, 40, 41, 42, 43, 44, 45, 46],
75: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 49],
76: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 40, 41, 42, 43],
77: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43],
78: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 17, 19, 21, 23, 25, 26, 28, 30, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42],
79: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27],
80: [1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 15, 16, 18, 20, 22, 24, 26, 28, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40],
81: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 44],
82: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31],
83: [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 27, 29, 31, 33, 35, 36, 37, 38, 1, 2, 3, 4],
84: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40],
85: [21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20],
86: [31, 32, 33, 34, 35, 36, 1, 2, 3, 4, 6, 8, 10, 12, 14, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
87: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 40, 41, 42, 43, 44],
88: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 28, 30, 32, 34, 35, 36, 37],
89: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 23, 25, 27, 29, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43],
90: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32],
91: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 23, 25, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40],
92: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 20, 21, 23, 25, 27, 29, 31, 32, 33, 34, 36, 38, 40, 42],
93: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 22, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36],
94: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 44, 45, 46],
97: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 35, 36, 37, 38, 39, 40],
}
Given both the NORMAL_SORTING_CONFIG and STROKE_SORTING_CONFIG it is just a matter of copying all the slices in the correct order to a different path, i.e., brain_ct_data_fixed.
import os
import shutil
def sort_slices(input_path, output_path, patient_id, order):
"""Copy the slices in the correct order"""
# Create output folder for sorted images (if it does not exist)
if not os.path.exists(output_path):
os.makedirs(output_path, exist_ok=True)
# Move the image to the output path with a name based on the correct sorting order
for new_id in range(1, len(order)+1):
old_id = order[new_id-1]
shutil.copyfile(f'{input_path}{os.sep}{patient_id} ({old_id}).jpg', f'{output_path}{os.sep}{patient_id} ({new_id}).jpg')
# Normal slices sorting
for patient_id, order in NORMAL_SORTING_CONFIG.items():
sort_slices(
input_path=NORMAL_INPUT_PATH,
output_path=NORMAL_OUTPUT_PATH,
patient_id=patient_id,
order=order)
# Stroke slices sorting
for patient_id, order in STROKE_SORTING_CONFIG.items():
sort_slices(
input_path=STROKE_INPUT_PATH,
output_path=STROKE_OUTPUT_PATH,
patient_id=patient_id,
order=order)
Let’s try to plot again CT slices for both patients 49 and 50:
plot_scan_from_path(slices_path=NORMAL_OUTPUT_PATH, patient_id=49)
No such file: '/content/brain_ct_data_fixed/Normal/49 (34).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/49 (35).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/49 (36).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/49 (37).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/49 (38).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/49 (39).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/49 (40).jpg'
plot_scan_from_path(slices_path=NORMAL_OUTPUT_PATH, patient_id=50)
No such file: '/content/brain_ct_data_fixed/Normal/50 (27).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (28).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (29).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (30).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (31).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (32).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (33).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (34).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (35).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (36).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (37).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (38).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (39).jpg'
No such file: '/content/brain_ct_data_fixed/Normal/50 (40).jpg'
Hopefully, the dataset should be fixed now.
!zip -r brain_ct_data_fixed.zip brain_ct_data_fixed
adding: brain_ct_data_fixed/ (stored 0%)
adding: brain_ct_data_fixed/Normal/ (stored 0%)
adding: brain_ct_data_fixed/Normal/113 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/65 (26).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/121 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/105 (12).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/64 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/109 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/64 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/100 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/112 (22).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/61 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/110 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (6).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/53 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/98 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (5).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/98 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/49 (31).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/57 (34).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/114 (27).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/124 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/105 (26).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/123 (32).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/61 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/118 (5).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/123 (36).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/50 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/116 (28).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/105 (18).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/60 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/60 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (32).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/53 (26).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/53 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/113 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/119 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/118 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/54 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/130 (15).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/49 (29).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/125 (32).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/105 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/55 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (27).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/114 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/102 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/101 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/119 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/52 (28).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/52 (15).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/116 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (22).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/104 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/95 (29).jpg (deflated 40%)
adding: brain_ct_data_fixed/Normal/112 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/125 (36).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/119 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/104 (28).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/121 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/54 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/101 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/114 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/120 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/56 (31).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/128 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/104 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/104 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/100 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/51 (5).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/125 (2).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/65 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/113 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/55 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/118 (30).jpg (deflated 33%)
adding: brain_ct_data_fixed/Normal/104 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/113 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/129 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/107 (30).jpg (deflated 33%)
adding: brain_ct_data_fixed/Normal/59 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/100 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/54 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/52 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/99 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/53 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/103 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/50 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/114 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/96 (31).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/95 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/53 (22).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/95 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/115 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/104 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/124 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/130 (30).jpg (deflated 28%)
adding: brain_ct_data_fixed/Normal/64 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/118 (9).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/95 (28).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/127 (29).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/56 (28).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/95 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/104 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/106 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/50 (25).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/63 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/114 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/127 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/51 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/109 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/112 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/100 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/59 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/123 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/95 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/101 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/121 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/108 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/116 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/117 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/52 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/111 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/60 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/104 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (29).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/115 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/99 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/55 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/54 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/123 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/52 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/50 (24).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/104 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/119 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/59 (4).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/61 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/127 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/121 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (23).jpg (deflated 34%)
adding: brain_ct_data_fixed/Normal/61 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/65 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/99 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/57 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/60 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/63 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/56 (14).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/109 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/99 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/55 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/115 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/64 (22).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/114 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/103 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/106 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/59 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/103 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/125 (24).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/121 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (3).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/124 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/103 (34).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/109 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (22).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/115 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/130 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/55 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/54 (27).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/56 (3).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/56 (18).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/112 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/96 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/129 (24).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/127 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/117 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/56 (11).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/106 (6).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/59 (26).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/51 (3).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/130 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/130 (27).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/65 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/117 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/127 (9).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/121 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/59 (2).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/95 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/117 (29).jpg (deflated 32%)
adding: brain_ct_data_fixed/Normal/110 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (33).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/105 (24).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/102 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/104 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/121 (30).jpg (deflated 42%)
adding: brain_ct_data_fixed/Normal/121 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (9).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/63 (32).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/53 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/65 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/103 (31).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/103 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/104 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/130 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/115 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/50 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/113 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/125 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/105 (19).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/118 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/101 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/107 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/98 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/109 (27).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/60 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/56 (17).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/56 (9).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/96 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/54 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/52 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/59 (18).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/59 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/96 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/126 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/126 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/105 (3).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/95 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/112 (21).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/99 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/56 (29).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/57 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/98 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/101 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/64 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/126 (28).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/96 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/109 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (35).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/125 (12).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/50 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/112 (23).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/111 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/65 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/111 (27).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/55 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/52 (27).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/108 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/63 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/95 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/100 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/121 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/129 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/119 (29).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/110 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/103 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/106 (24).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/50 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/102 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/110 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/54 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/60 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/112 (20).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/119 (6).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/112 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/123 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/128 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/51 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/123 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/60 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/109 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/127 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/112 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/96 (29).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/95 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/118 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/116 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (8).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/57 (25).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/103 (30).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/127 (30).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/112 (17).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/65 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/117 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/115 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (8).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/130 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/56 (4).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/123 (28).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/111 (11).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/123 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/100 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/114 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/100 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/54 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/124 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/117 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/102 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/106 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/59 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/115 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/125 (6).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/60 (28).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/127 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/55 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/54 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/102 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/106 (1).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/52 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/128 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/120 (29).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/118 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/107 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/52 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/110 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/103 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/112 (18).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/61 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (38).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/107 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/128 (25).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/95 (24).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/128 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/53 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/110 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/100 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/108 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/51 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/98 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/114 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (29).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/50 (6).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/102 (30).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/103 (26).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/111 (18).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/50 (26).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/49 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/101 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (15).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/122 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/64 (23).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/104 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/54 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/50 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/95 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/98 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/102 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/105 (10).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/61 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/105 (21).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/103 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/116 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/105 (27).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/51 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/56 (7).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/63 (23).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/118 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/130 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (28).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/103 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/57 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/114 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/62 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/108 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/99 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/128 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/59 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/50 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/53 (23).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/56 (5).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/118 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/101 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/109 (25).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/113 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/56 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/117 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/54 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/108 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (27).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/95 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/50 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/113 (28).jpg (deflated 32%)
adding: brain_ct_data_fixed/Normal/117 (25).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/128 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/63 (27).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/123 (30).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/119 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/129 (27).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/65 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/120 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/56 (8).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/109 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/115 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/126 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (20).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/50 (1).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/53 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/63 (24).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/115 (31).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/57 (24).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/104 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/51 (27).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/127 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/50 (9).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/115 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/124 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/52 (23).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/59 (25).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/53 (29).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/113 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (30).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/62 (19).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/130 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/99 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/105 (16).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/108 (29).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/95 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/118 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/115 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/125 (39).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/111 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/64 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/111 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/56 (33).jpg (deflated 34%)
adding: brain_ct_data_fixed/Normal/128 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/108 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/99 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/101 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/102 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/57 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (2).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/109 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/64 (21).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/119 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/103 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/95 (6).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/52 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/124 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/62 (20).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/57 (22).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/51 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/102 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/120 (30).jpg (deflated 28%)
adding: brain_ct_data_fixed/Normal/107 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (30).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/55 (28).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/125 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/52 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/129 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/126 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/54 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/126 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/109 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/50 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/108 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/63 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/57 (31).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/101 (29).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/112 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/109 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/61 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/65 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/128 (27).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/57 (32).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/127 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/126 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/128 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/123 (33).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/106 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/107 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (11).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/105 (11).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/59 (3).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/106 (28).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/110 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/55 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/56 (1).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/100 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/99 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/99 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/100 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/113 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/54 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/52 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/128 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/124 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/98 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/110 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/100 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/126 (30).jpg (deflated 32%)
adding: brain_ct_data_fixed/Normal/54 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/96 (4).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/116 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/49 (12).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/95 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/119 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/55 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/118 (11).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/125 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/112 (5).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/113 (24).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/102 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/98 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/101 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/121 (25).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/110 (28).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/62 (1).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/52 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/120 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/114 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/110 (24).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/51 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/126 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/112 (4).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/108 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/64 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/109 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/108 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/49 (20).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/61 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/107 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/115 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/120 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/130 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/130 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/120 (28).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/111 (22).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/53 (30).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/60 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/101 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/99 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/100 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/120 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/65 (28).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/60 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/126 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/129 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/123 (29).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (31).jpg (deflated 33%)
adding: brain_ct_data_fixed/Normal/105 (25).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/113 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/114 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/127 (3).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/62 (22).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/123 (39).jpg (deflated 34%)
adding: brain_ct_data_fixed/Normal/65 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/119 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/49 (27).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/55 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/130 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/109 (28).jpg (deflated 38%)
adding: brain_ct_data_fixed/Normal/114 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (35).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/126 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/57 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/96 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/111 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/104 (27).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/52 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/129 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (27).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/111 (33).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/96 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (28).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/103 (27).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/100 (26).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/129 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/56 (13).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/60 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/102 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/104 (29).jpg (deflated 30%)
adding: brain_ct_data_fixed/Normal/53 (18).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/125 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (26).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (18).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/129 (1).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/117 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/103 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/103 (25).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/50 (3).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/60 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/64 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (29).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/100 (4).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/102 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/52 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/63 (30).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/109 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/113 (1).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/65 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/112 (14).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/65 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/100 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (36).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/102 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/115 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (23).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/128 (23).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/101 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/123 (27).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/101 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/114 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/50 (4).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/115 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/114 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/103 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/121 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/120 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (24).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/123 (3).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/111 (23).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/54 (28).jpg (deflated 28%)
adding: brain_ct_data_fixed/Normal/105 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/128 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/110 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/55 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/100 (28).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/127 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/126 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/121 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/105 (30).jpg (deflated 50%)
adding: brain_ct_data_fixed/Normal/115 (27).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/127 (31).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/49 (23).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/99 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/118 (29).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/62 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/109 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/101 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/65 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/126 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/51 (30).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/113 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/62 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/107 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/99 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/128 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/118 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/65 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/56 (6).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/122 (13).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/57 (35).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/130 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/59 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/64 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/130 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (29).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/99 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/128 (24).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/96 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/98 (27).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/126 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/127 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/55 (30).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/103 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/105 (9).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/52 (3).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/103 (35).jpg (deflated 48%)
adding: brain_ct_data_fixed/Normal/112 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/116 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/53 (24).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/124 (28).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/125 (1).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/52 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/126 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/107 (28).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/64 (25).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/126 (29).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/125 (9).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/65 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/130 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/129 (29).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/95 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/59 (19).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/50 (7).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/63 (22).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/49 (17).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/55 (1).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/100 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/52 (26).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/54 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/123 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/126 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/96 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/100 (27).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/111 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/124 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/103 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/124 (30).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/111 (24).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/56 (32).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/57 (2).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/121 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/124 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/101 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/110 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/120 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/102 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/54 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/110 (27).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/63 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/128 (26).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/107 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/118 (8).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/100 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/122 (28).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/126 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/59 (24).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/102 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/110 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (3).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/104 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/100 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/118 (10).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/105 (2).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/54 (24).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/115 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/117 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/110 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/99 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (5).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/117 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/101 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/125 (27).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/54 (25).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/53 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/59 (27).jpg (deflated 36%)
adding: brain_ct_data_fixed/Normal/105 (1).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/123 (34).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/65 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (28).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/130 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/113 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/124 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/118 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (29).jpg (deflated 32%)
adding: brain_ct_data_fixed/Normal/49 (19).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/124 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/99 (25).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/109 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/123 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (11).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/103 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/113 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/120 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/118 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/123 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/123 (26).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/61 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (4).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/103 (29).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/57 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/55 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/130 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/130 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/120 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/120 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (25).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/61 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/111 (30).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/49 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (9).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/99 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/113 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/125 (7).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/109 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/130 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/128 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/113 (27).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/123 (31).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/57 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/106 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/100 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/130 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/55 (26).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/57 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/51 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/112 (19).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/127 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/102 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/106 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/129 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/128 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/126 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/65 (30).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/126 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/115 (32).jpg (deflated 38%)
adding: brain_ct_data_fixed/Normal/127 (4).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/110 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/111 (8).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/98 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/116 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/108 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/99 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/105 (29).jpg (deflated 37%)
adding: brain_ct_data_fixed/Normal/50 (8).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/111 (21).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/102 (31).jpg (deflated 33%)
adding: brain_ct_data_fixed/Normal/115 (29).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/125 (34).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/64 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/53 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/107 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/113 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/128 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/116 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/101 (28).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/111 (28).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/121 (28).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/122 (27).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/106 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/120 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/114 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/111 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/104 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/59 (22).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/64 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (25).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/51 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/104 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/56 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/117 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/126 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/109 (23).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/117 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/51 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/110 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (9).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/120 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/106 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/105 (6).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/119 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/57 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/123 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/103 (8).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/95 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/118 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (13).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/116 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/61 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/113 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/65 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/60 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/109 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (29).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (29).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/54 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/56 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/49 (24).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/60 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/119 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/62 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/127 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (2).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/64 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/114 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/121 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/101 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/96 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/124 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/112 (26).jpg (deflated 49%)
adding: brain_ct_data_fixed/Normal/99 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/122 (4).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/124 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/95 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/119 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/95 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/99 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (16).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/125 (5).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/54 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/122 (24).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/125 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/130 (29).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/130 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/98 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/114 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/110 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/111 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/61 (30).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/116 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/105 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/108 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/99 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/122 (11).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/100 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/50 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/102 (28).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/115 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/127 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (12).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/98 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (21).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/62 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/96 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/119 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/103 (32).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/125 (3).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/103 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/51 (1).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/106 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/115 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/103 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/123 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/55 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/61 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/63 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/117 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/100 (25).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/127 (2).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/125 (30).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/57 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/62 (17).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/108 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/54 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/61 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/59 (5).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/98 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/55 (32).jpg (deflated 39%)
adding: brain_ct_data_fixed/Normal/107 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/105 (20).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/101 (31).jpg (deflated 37%)
adding: brain_ct_data_fixed/Normal/125 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/63 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/98 (25).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/62 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/51 (32).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/50 (5).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/118 (1).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/55 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/113 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/123 (2).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/114 (29).jpg (deflated 30%)
adding: brain_ct_data_fixed/Normal/101 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/118 (7).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/50 (2).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/117 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/99 (27).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/122 (8).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/53 (33).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/103 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/49 (14).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/101 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/128 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/125 (25).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (1).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/95 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/118 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/109 (24).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/106 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/108 (28).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/109 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/64 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/119 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/54 (23).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/53 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/118 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/112 (16).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/123 (17).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/62 (15).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/113 (25).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/99 (29).jpg (deflated 32%)
adding: brain_ct_data_fixed/Normal/56 (16).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/119 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/49 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/106 (26).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/111 (10).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/100 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/130 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (18).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/52 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/115 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/101 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/125 (4).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/106 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/127 (32).jpg (deflated 30%)
adding: brain_ct_data_fixed/Normal/59 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (8).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/109 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/122 (18).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/56 (30).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/119 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/126 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/53 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/127 (10).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/114 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/112 (1).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/61 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/64 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/55 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/106 (25).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/121 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/117 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/103 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/56 (27).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/51 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/96 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/110 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/51 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/104 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/104 (25).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/109 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/50 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/51 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/104 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/122 (16).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/123 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/114 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/120 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/128 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/99 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/110 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (13).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/119 (1).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/110 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/56 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/53 (25).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/64 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/120 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/51 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/108 (7).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/55 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/57 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/60 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/101 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/126 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/57 (27).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/109 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/111 (19).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/99 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/64 (19).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/49 (8).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/65 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/104 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/130 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/127 (27).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/106 (29).jpg (deflated 32%)
adding: brain_ct_data_fixed/Normal/52 (24).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/63 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/95 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/107 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/55 (29).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/61 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/123 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/110 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (23).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/115 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/60 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/101 (30).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/103 (28).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/102 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/95 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/102 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/111 (32).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/108 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/51 (8).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/53 (19).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/107 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/60 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/123 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (35).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/101 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/106 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/111 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/113 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/107 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/112 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/112 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/126 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/124 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (33).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/128 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/117 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/108 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/125 (10).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/56 (24).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/108 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/122 (19).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/129 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/51 (31).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/102 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/115 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/61 (29).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/54 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/95 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/104 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/100 (29).jpg (deflated 30%)
adding: brain_ct_data_fixed/Normal/62 (14).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/104 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/64 (20).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/124 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/52 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/59 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/123 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/52 (1).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/118 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/118 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/110 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/115 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/116 (29).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/128 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/107 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/114 (25).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/130 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/100 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/128 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/106 (27).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/52 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/63 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/114 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/108 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/65 (15).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (4).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/115 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/55 (27).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/120 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/127 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (4).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/109 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/107 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/53 (1).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/55 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/54 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (37).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/125 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/98 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/53 (32).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/50 (23).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/106 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/126 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/122 (21).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/105 (23).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/119 (28).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/116 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (11).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/51 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (31).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/96 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/116 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/103 (33).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/63 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/125 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/55 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/112 (25).jpg (deflated 35%)
adding: brain_ct_data_fixed/Normal/112 (24).jpg (deflated 27%)
adding: brain_ct_data_fixed/Normal/111 (26).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/121 (27).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/57 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/126 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/121 (8).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (25).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/57 (29).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/114 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/63 (28).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/125 (37).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/124 (29).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/57 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/55 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/122 (17).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/102 (1).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/50 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/113 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/114 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/107 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/63 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/119 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/113 (26).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/60 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/115 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/54 (22).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/129 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/106 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/63 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/103 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/95 (25).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/111 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/56 (12).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/130 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/130 (9).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/100 (30).jpg (deflated 42%)
adding: brain_ct_data_fixed/Normal/98 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/53 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/129 (30).jpg (deflated 36%)
adding: brain_ct_data_fixed/Normal/116 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/104 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/96 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/96 (33).jpg (deflated 44%)
adding: brain_ct_data_fixed/Normal/130 (25).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/101 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/117 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/115 (28).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/57 (26).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/53 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/130 (28).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/107 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/116 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/108 (27).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/116 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/110 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/103 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/122 (1).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/115 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/100 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/62 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/113 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/107 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/128 (22).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/104 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/57 (28).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/125 (31).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/96 (30).jpg (deflated 18%)
adding: brain_ct_data_fixed/Normal/106 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (26).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/116 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (7).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/61 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/64 (24).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/110 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/105 (28).jpg (deflated 30%)
adding: brain_ct_data_fixed/Normal/126 (26).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/122 (12).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/51 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/123 (1).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/112 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/55 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/127 (5).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/107 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/63 (34).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/53 (28).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (33).jpg (deflated 26%)
adding: brain_ct_data_fixed/Normal/124 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/128 (28).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/118 (28).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/61 (31).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/99 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/61 (26).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/108 (8).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/106 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/120 (2).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/96 (32).jpg (deflated 29%)
adding: brain_ct_data_fixed/Normal/111 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/96 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/115 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/130 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/128 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/124 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/106 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/59 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/98 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/119 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/125 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/62 (21).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/120 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/122 (6).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/59 (23).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/116 (30).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/117 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/49 (26).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/52 (25).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/115 (30).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/59 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/126 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/116 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/98 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/113 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/105 (4).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/110 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/65 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/96 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/98 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/64 (26).jpg (deflated 29%)
adding: brain_ct_data_fixed/Normal/117 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/117 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/118 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/111 (20).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/54 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/114 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/103 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/106 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/98 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/122 (2).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/64 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/122 (10).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/116 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/103 (6).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/124 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/106 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/98 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/105 (22).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/101 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/124 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/56 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/110 (4).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/117 (28).jpg (deflated 25%)
adding: brain_ct_data_fixed/Normal/120 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/107 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/120 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/121 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/52 (29).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/49 (7).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/96 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/124 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/55 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/49 (16).jpg (deflated 4%)
adding: brain_ct_data_fixed/Normal/55 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/109 (26).jpg (deflated 21%)
adding: brain_ct_data_fixed/Normal/95 (27).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/114 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/64 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/107 (29).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/123 (25).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/99 (28).jpg (deflated 24%)
adding: brain_ct_data_fixed/Normal/105 (14).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/111 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/54 (26).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/114 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/52 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/125 (38).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/51 (9).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/61 (27).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/53 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/118 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/101 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/114 (28).jpg (deflated 23%)
adding: brain_ct_data_fixed/Normal/116 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/102 (29).jpg (deflated 20%)
adding: brain_ct_data_fixed/Normal/125 (26).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/105 (17).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/111 (29).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/105 (15).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/52 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/115 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/56 (19).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/103 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/112 (3).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/102 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/105 (13).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/102 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/56 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/99 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/127 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/49 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/122 (26).jpg (deflated 19%)
adding: brain_ct_data_fixed/Normal/114 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/129 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/56 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/50 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/95 (2).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/115 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (3).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/53 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/96 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/95 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/122 (14).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/96 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/52 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/111 (31).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/95 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/118 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/129 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/99 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/111 (25).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/61 (7).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/101 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/59 (20).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/113 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/107 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/101 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/100 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/62 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/55 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/121 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/51 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/104 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/60 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/57 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/110 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (30).jpg (deflated 22%)
adding: brain_ct_data_fixed/Normal/61 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/113 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/101 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/120 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/126 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/111 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/64 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/59 (21).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/106 (23).jpg (deflated 12%)
adding: brain_ct_data_fixed/Normal/56 (2).jpg (deflated 16%)
adding: brain_ct_data_fixed/Normal/61 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/55 (31).jpg (deflated 31%)
adding: brain_ct_data_fixed/Normal/125 (28).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/52 (30).jpg (deflated 41%)
adding: brain_ct_data_fixed/Normal/56 (10).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/63 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/109 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/64 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/118 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/49 (10).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/59 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/121 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/57 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/100 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/121 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/60 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/108 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/124 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/111 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Normal/121 (1).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/119 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Normal/106 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Normal/118 (27).jpg (deflated 17%)
adding: brain_ct_data_fixed/Normal/60 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/123 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/55 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/63 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/59 (1).jpg (deflated 15%)
adding: brain_ct_data_fixed/Normal/128 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/96 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/104 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Normal/57 (33).jpg (deflated 13%)
adding: brain_ct_data_fixed/Normal/125 (40).jpg (deflated 30%)
adding: brain_ct_data_fixed/Normal/108 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/129 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/126 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Normal/98 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/60 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Normal/119 (31).jpg (deflated 29%)
adding: brain_ct_data_fixed/Normal/63 (31).jpg (deflated 10%)
adding: brain_ct_data_fixed/Normal/104 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Normal/130 (31).jpg (deflated 36%)
adding: brain_ct_data_fixed/Stroke/ (stored 0%)
adding: brain_ct_data_fixed/Stroke/94 (26).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/71 (27).jpg (deflated 22%)
adding: brain_ct_data_fixed/Stroke/69 (22).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/93 (21).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/93 (22).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/83 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/69 (16).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/70 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/93 (23).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/71 (2).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/83 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/94 (1).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/94 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/89 (28).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/86 (14).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/85 (6).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/74 (29).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/94 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/76 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/75 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/88 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/68 (25).jpg (deflated 33%)
adding: brain_ct_data_fixed/Stroke/88 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/91 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/76 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/58 (28).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/58 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/72 (5).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/84 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/71 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/58 (25).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/86 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/97 (27).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/69 (1).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/85 (17).jpg (deflated 30%)
adding: brain_ct_data_fixed/Stroke/81 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/84 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/69 (25).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/97 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/70 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/86 (9).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/93 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/78 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/91 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/73 (9).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/88 (3).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/97 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/82 (5).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/75 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/69 (26).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/85 (19).jpg (deflated 46%)
adding: brain_ct_data_fixed/Stroke/88 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/78 (7).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/74 (28).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/85 (4).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/88 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/89 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/85 (11).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/77 (30).jpg (deflated 27%)
adding: brain_ct_data_fixed/Stroke/77 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/70 (29).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/82 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/77 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/77 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/70 (27).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/91 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/77 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/86 (13).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/84 (36).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/71 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/92 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/66 (16).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/69 (10).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/91 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/93 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/69 (5).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/84 (22).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/85 (5).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/88 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/90 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/84 (19).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/69 (17).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/76 (3).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/89 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (31).jpg (deflated 27%)
adding: brain_ct_data_fixed/Stroke/94 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/88 (30).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/70 (2).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/72 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/72 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/77 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/90 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/79 (14).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/66 (27).jpg (deflated 25%)
adding: brain_ct_data_fixed/Stroke/84 (33).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/89 (32).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/82 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/91 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/80 (26).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/66 (10).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/58 (27).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/78 (27).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/72 (30).jpg (deflated 34%)
adding: brain_ct_data_fixed/Stroke/79 (17).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/75 (8).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/72 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/94 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/83 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/79 (19).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/73 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/66 (5).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/66 (8).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/83 (30).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/82 (11).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/94 (25).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/76 (11).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/58 (2).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/81 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/74 (3).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/71 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/71 (23).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/72 (29).jpg (deflated 26%)
adding: brain_ct_data_fixed/Stroke/58 (3).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/74 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/82 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/83 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/92 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/79 (12).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/78 (26).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/73 (16).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/84 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/58 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/66 (7).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/77 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/78 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/89 (1).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/78 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/79 (1).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/97 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/73 (4).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/75 (9).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/83 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/70 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/72 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/90 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/75 (28).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/94 (33).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/66 (12).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/87 (4).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/75 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/73 (6).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/75 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/77 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/80 (25).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/79 (18).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/71 (26).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/93 (26).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/97 (3).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/68 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/84 (24).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/75 (30).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/89 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/94 (28).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/70 (31).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/71 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/91 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/88 (28).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/72 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/75 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/94 (29).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/88 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (29).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/92 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/82 (27).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/97 (8).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/66 (11).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/71 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/71 (25).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/77 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/81 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/69 (30).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/81 (29).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/77 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/69 (27).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/97 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/79 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/92 (2).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/90 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/83 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/77 (7).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/92 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/78 (31).jpg (deflated 30%)
adding: brain_ct_data_fixed/Stroke/75 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/67 (23).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/83 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/75 (2).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/72 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/66 (9).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/69 (32).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/94 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/66 (21).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/92 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/88 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/94 (24).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/70 (5).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/84 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/69 (28).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/91 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/58 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/80 (8).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/83 (29).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/75 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/87 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/89 (13).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/91 (30).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/67 (17).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/92 (30).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/84 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/70 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/77 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/71 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/72 (8).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/83 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/94 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/66 (23).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/91 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/82 (9).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/68 (20).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/82 (10).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/81 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/94 (30).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/93 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/77 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/83 (32).jpg (deflated 34%)
adding: brain_ct_data_fixed/Stroke/78 (11).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/94 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/70 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/90 (26).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/75 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/93 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/97 (1).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/67 (15).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/81 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/86 (6).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/91 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/58 (26).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/91 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/75 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/77 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/93 (29).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/91 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/78 (5).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/70 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/58 (8).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/69 (2).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/94 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/69 (9).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/79 (13).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/66 (13).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/90 (10).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/77 (28).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/97 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/73 (8).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/80 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/86 (29).jpg (deflated 43%)
adding: brain_ct_data_fixed/Stroke/67 (11).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/67 (8).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/69 (19).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/93 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/72 (16).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/75 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/68 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/73 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/83 (1).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/81 (8).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/92 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/97 (29).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/82 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/88 (27).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/86 (20).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/87 (6).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/80 (22).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/75 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/88 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/72 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/71 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/94 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/76 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/73 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/86 (17).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/58 (1).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/86 (26).jpg (deflated 23%)
adding: brain_ct_data_fixed/Stroke/82 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/80 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/73 (10).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/80 (4).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/93 (27).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/82 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/85 (2).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/73 (14).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/76 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/86 (3).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/71 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/90 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/92 (24).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/87 (1).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/86 (4).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/67 (28).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/80 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/83 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/97 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/68 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/91 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/89 (18).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/89 (27).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/91 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/86 (5).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/78 (30).jpg (deflated 24%)
adding: brain_ct_data_fixed/Stroke/92 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/70 (11).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/67 (22).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/70 (32).jpg (deflated 27%)
adding: brain_ct_data_fixed/Stroke/71 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/70 (6).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/74 (20).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/93 (18).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/75 (27).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/97 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/82 (8).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/82 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/93 (28).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/79 (26).jpg (deflated 36%)
adding: brain_ct_data_fixed/Stroke/83 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/88 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/77 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/67 (16).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/66 (19).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/68 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/91 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/76 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/89 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/70 (8).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/77 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/87 (29).jpg (deflated 22%)
adding: brain_ct_data_fixed/Stroke/86 (12).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/86 (19).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/97 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/79 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/74 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/90 (8).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/74 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/69 (24).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/82 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/84 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/94 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/88 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/88 (31).jpg (deflated 19%)
adding: brain_ct_data_fixed/Stroke/70 (4).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/66 (6).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/69 (23).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/72 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/88 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/86 (11).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/82 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/66 (2).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/93 (30).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/94 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/71 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/85 (10).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/87 (2).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/80 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/66 (14).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/76 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/79 (21).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/68 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/68 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/66 (25).jpg (deflated 19%)
adding: brain_ct_data_fixed/Stroke/97 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/76 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/70 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/89 (34).jpg (deflated 24%)
adding: brain_ct_data_fixed/Stroke/82 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/76 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/84 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/76 (29).jpg (deflated 29%)
adding: brain_ct_data_fixed/Stroke/78 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/83 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/87 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/72 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/90 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/81 (18).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/75 (25).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/97 (31).jpg (deflated 32%)
adding: brain_ct_data_fixed/Stroke/94 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/81 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/78 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/58 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/92 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/88 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/87 (8).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/83 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/84 (2).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/89 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/81 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/89 (10).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/93 (32).jpg (deflated 29%)
adding: brain_ct_data_fixed/Stroke/87 (32).jpg (deflated 46%)
adding: brain_ct_data_fixed/Stroke/97 (4).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/67 (5).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/88 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/93 (19).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/81 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/92 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/58 (18).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/92 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/67 (24).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/73 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/97 (30).jpg (deflated 22%)
adding: brain_ct_data_fixed/Stroke/78 (3).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/91 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/69 (7).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/74 (22).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/82 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/83 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/67 (9).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/81 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/90 (25).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/68 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/75 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/79 (2).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/72 (28).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/68 (24).jpg (deflated 25%)
adding: brain_ct_data_fixed/Stroke/87 (14).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/90 (1).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/79 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/77 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/86 (28).jpg (deflated 33%)
adding: brain_ct_data_fixed/Stroke/84 (32).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/73 (29).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/90 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/68 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/67 (1).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/84 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/68 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/83 (31).jpg (deflated 24%)
adding: brain_ct_data_fixed/Stroke/75 (33).jpg (deflated 30%)
adding: brain_ct_data_fixed/Stroke/72 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/86 (7).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/89 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/69 (14).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/82 (19).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/87 (24).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/89 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/67 (3).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/85 (18).jpg (deflated 36%)
adding: brain_ct_data_fixed/Stroke/74 (9).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/91 (32).jpg (deflated 33%)
adding: brain_ct_data_fixed/Stroke/92 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/77 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/75 (7).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/91 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/90 (23).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/69 (3).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/68 (18).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/67 (25).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/79 (23).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/89 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/84 (18).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/78 (10).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/71 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/97 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/78 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/80 (19).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/84 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/78 (28).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/78 (6).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/76 (27).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/90 (24).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/72 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/93 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/66 (3).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/68 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/88 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/89 (2).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/76 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/66 (28).jpg (deflated 31%)
adding: brain_ct_data_fixed/Stroke/84 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/72 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/73 (13).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/69 (29).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/68 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/66 (4).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/66 (1).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/78 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/58 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/92 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/70 (1).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/83 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/84 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/58 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/82 (28).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/79 (22).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/68 (21).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/83 (27).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/69 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/86 (25).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/75 (3).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/87 (3).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/93 (7).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/86 (10).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/82 (20).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/88 (5).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/72 (2).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/94 (34).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/76 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/80 (2).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/74 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/72 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/66 (26).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/87 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/93 (2).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/86 (27).jpg (deflated 27%)
adding: brain_ct_data_fixed/Stroke/70 (17).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/58 (29).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/73 (33).jpg (deflated 58%)
adding: brain_ct_data_fixed/Stroke/79 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/73 (28).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/88 (9).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/74 (7).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/89 (35).jpg (deflated 30%)
adding: brain_ct_data_fixed/Stroke/67 (6).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/73 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/97 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/74 (31).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/84 (31).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/80 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/83 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/73 (31).jpg (deflated 31%)
adding: brain_ct_data_fixed/Stroke/68 (23).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/93 (16).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/76 (7).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/75 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/83 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/97 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/78 (18).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/94 (7).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/67 (18).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/92 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/76 (5).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/68 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/89 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/90 (6).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/89 (31).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/87 (31).jpg (deflated 33%)
adding: brain_ct_data_fixed/Stroke/81 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/67 (27).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/67 (14).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/94 (27).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/73 (11).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/72 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/84 (28).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/78 (29).jpg (deflated 19%)
adding: brain_ct_data_fixed/Stroke/87 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/83 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/92 (16).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/90 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/97 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/90 (4).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/85 (13).jpg (deflated 19%)
adding: brain_ct_data_fixed/Stroke/70 (21).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/90 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/79 (16).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/91 (26).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/72 (25).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/72 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/76 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/70 (33).jpg (deflated 35%)
adding: brain_ct_data_fixed/Stroke/71 (8).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/68 (3).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/88 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/88 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/93 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/90 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/73 (30).jpg (deflated 25%)
adding: brain_ct_data_fixed/Stroke/80 (11).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/91 (4).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/84 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/75 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/81 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/86 (18).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/80 (28).jpg (deflated 30%)
adding: brain_ct_data_fixed/Stroke/71 (29).jpg (deflated 37%)
adding: brain_ct_data_fixed/Stroke/81 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/75 (6).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/76 (28).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/97 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/67 (10).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/91 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/77 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/69 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/87 (10).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/58 (33).jpg (deflated 27%)
adding: brain_ct_data_fixed/Stroke/88 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/75 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/93 (31).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/84 (23).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/70 (34).jpg (deflated 51%)
adding: brain_ct_data_fixed/Stroke/83 (14).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/80 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/97 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/91 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/94 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/81 (6).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/87 (16).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/80 (29).jpg (deflated 41%)
adding: brain_ct_data_fixed/Stroke/73 (25).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/74 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/70 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/92 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/75 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/89 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/70 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/78 (25).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/83 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/89 (30).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/93 (5).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/86 (23).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/92 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/79 (25).jpg (deflated 28%)
adding: brain_ct_data_fixed/Stroke/78 (8).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/89 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/74 (27).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/88 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/67 (12).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/84 (27).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/78 (9).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/73 (2).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/70 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/58 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/80 (3).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/87 (12).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/77 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/91 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/74 (23).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/70 (30).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/68 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/97 (6).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/82 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/67 (4).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/68 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/97 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/71 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/85 (3).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/89 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/79 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/78 (2).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/82 (18).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/90 (28).jpg (deflated 33%)
adding: brain_ct_data_fixed/Stroke/82 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/58 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/87 (11).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/71 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/93 (15).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/91 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/84 (26).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/73 (1).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/83 (2).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/88 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/93 (24).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/93 (25).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/72 (22).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/70 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/66 (15).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/81 (12).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/69 (8).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/80 (10).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/87 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/68 (4).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/89 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/72 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/68 (26).jpg (deflated 52%)
adding: brain_ct_data_fixed/Stroke/87 (13).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/84 (20).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/68 (13).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/73 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/77 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/58 (31).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/86 (8).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/90 (21).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/77 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/83 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/73 (27).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/81 (28).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/58 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/84 (29).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/58 (7).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/82 (25).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/93 (17).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/89 (26).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/66 (22).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/79 (24).jpg (deflated 22%)
adding: brain_ct_data_fixed/Stroke/81 (10).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/76 (19).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/84 (34).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/82 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/93 (11).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/69 (34).jpg (deflated 30%)
adding: brain_ct_data_fixed/Stroke/80 (27).jpg (deflated 24%)
adding: brain_ct_data_fixed/Stroke/81 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/83 (28).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/71 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/58 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/90 (7).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/91 (23).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/67 (2).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/85 (9).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/58 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/79 (4).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/92 (7).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/84 (14).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/75 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/74 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/67 (20).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/58 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/84 (25).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/93 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/76 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/77 (31).jpg (deflated 38%)
adding: brain_ct_data_fixed/Stroke/72 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/71 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/69 (20).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/71 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/70 (12).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/91 (2).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/74 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/58 (24).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/70 (10).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/87 (7).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/66 (29).jpg (deflated 38%)
adding: brain_ct_data_fixed/Stroke/58 (5).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/81 (20).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/76 (16).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/58 (34).jpg (deflated 37%)
adding: brain_ct_data_fixed/Stroke/67 (13).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/89 (8).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/80 (15).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/91 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/68 (19).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/77 (29).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/69 (11).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/58 (30).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/58 (32).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/85 (8).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/67 (7).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/90 (27).jpg (deflated 25%)
adding: brain_ct_data_fixed/Stroke/89 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/77 (20).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/81 (19).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/89 (29).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/94 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/78 (19).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/76 (17).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/76 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/80 (16).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/58 (22).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/69 (31).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/74 (2).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/80 (1).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/71 (22).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/77 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/87 (23).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/71 (12).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/73 (7).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/75 (29).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/75 (31).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/82 (6).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/72 (26).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/76 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/76 (23).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/97 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/87 (28).jpg (deflated 19%)
adding: brain_ct_data_fixed/Stroke/74 (13).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/74 (30).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/86 (24).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/74 (32).jpg (deflated 24%)
adding: brain_ct_data_fixed/Stroke/97 (12).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/78 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/93 (20).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/86 (22).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/79 (5).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/94 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/66 (24).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/74 (17).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/73 (19).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/74 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/93 (1).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/79 (20).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/84 (35).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/75 (32).jpg (deflated 21%)
adding: brain_ct_data_fixed/Stroke/77 (3).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/83 (8).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/87 (25).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/89 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/75 (26).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/76 (15).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/80 (18).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/97 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/78 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/90 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/69 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/91 (31).jpg (deflated 26%)
adding: brain_ct_data_fixed/Stroke/81 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/79 (3).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/80 (6).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/58 (4).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/81 (11).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/76 (21).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/73 (5).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/77 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/67 (21).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/79 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/71 (15).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/92 (28).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/73 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/82 (29).jpg (deflated 29%)
adding: brain_ct_data_fixed/Stroke/74 (8).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/69 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/82 (26).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/86 (21).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/66 (20).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/84 (30).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/81 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/88 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (11).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (6).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/78 (13).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/81 (14).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/73 (17).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/73 (18).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/74 (1).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/87 (27).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/66 (18).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/83 (5).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/85 (7).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/77 (8).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/78 (1).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/76 (8).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/70 (15).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/90 (11).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/94 (21).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/85 (16).jpg (deflated 25%)
adding: brain_ct_data_fixed/Stroke/86 (1).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/78 (4).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/77 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/88 (10).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/83 (15).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/74 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/89 (33).jpg (deflated 19%)
adding: brain_ct_data_fixed/Stroke/80 (24).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/94 (12).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/91 (33).jpg (deflated 41%)
adding: brain_ct_data_fixed/Stroke/81 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/88 (29).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/91 (1).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/92 (23).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/93 (10).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/73 (3).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/87 (5).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/89 (16).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/79 (6).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/85 (14).jpg (deflated 20%)
adding: brain_ct_data_fixed/Stroke/94 (31).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/69 (18).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/80 (9).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/80 (21).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/87 (30).jpg (deflated 27%)
adding: brain_ct_data_fixed/Stroke/97 (9).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/89 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/84 (21).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/78 (12).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/71 (24).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/88 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/70 (3).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/91 (28).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/72 (27).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/72 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/92 (5).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/85 (1).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/97 (20).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/67 (26).jpg (deflated 16%)
adding: brain_ct_data_fixed/Stroke/94 (32).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/58 (11).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/74 (24).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/81 (27).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/74 (10).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/74 (25).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/70 (9).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/84 (3).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/71 (28).jpg (deflated 28%)
adding: brain_ct_data_fixed/Stroke/74 (21).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/87 (18).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/82 (7).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/97 (18).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/91 (29).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/58 (14).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/90 (17).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/83 (17).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/70 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/85 (12).jpg (deflated 18%)
adding: brain_ct_data_fixed/Stroke/94 (9).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/74 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/84 (15).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/92 (27).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/66 (17).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/84 (5).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/74 (26).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/94 (22).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/81 (4).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/87 (15).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/85 (15).jpg (deflated 22%)
adding: brain_ct_data_fixed/Stroke/69 (15).jpg (deflated 4%)
adding: brain_ct_data_fixed/Stroke/73 (32).jpg (deflated 42%)
adding: brain_ct_data_fixed/Stroke/90 (5).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/76 (6).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/75 (19).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/80 (23).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/71 (9).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/89 (25).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/89 (24).jpg (deflated 8%)
adding: brain_ct_data_fixed/Stroke/86 (2).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/86 (16).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/88 (23).jpg (deflated 7%)
adding: brain_ct_data_fixed/Stroke/74 (33).jpg (deflated 29%)
adding: brain_ct_data_fixed/Stroke/67 (19).jpg (deflated 11%)
adding: brain_ct_data_fixed/Stroke/80 (20).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/73 (12).jpg (deflated 12%)
adding: brain_ct_data_fixed/Stroke/69 (21).jpg (deflated 5%)
adding: brain_ct_data_fixed/Stroke/68 (22).jpg (deflated 17%)
adding: brain_ct_data_fixed/Stroke/69 (33).jpg (deflated 22%)
adding: brain_ct_data_fixed/Stroke/91 (14).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/94 (2).jpg (deflated 14%)
adding: brain_ct_data_fixed/Stroke/94 (3).jpg (deflated 13%)
adding: brain_ct_data_fixed/Stroke/87 (9).jpg (deflated 15%)
adding: brain_ct_data_fixed/Stroke/90 (19).jpg (deflated 9%)
adding: brain_ct_data_fixed/Stroke/70 (26).jpg (deflated 10%)
adding: brain_ct_data_fixed/Stroke/72 (13).jpg (deflated 6%)
adding: brain_ct_data_fixed/Stroke/87 (19).jpg (deflated 10%)
The fixed dataset is publicly available here.
Dataset loading and preprocessing
In case the previous section has been skipped, it is possible to directly download the fixed dataset:
import os
import zipfile
import tensorflow as tf
# Download dataset from GitHub
url = "https://github.com/Peco602/brain-stroke-detection-3d-cnn/releases/download/v0.0.1/brain_ct_data_fixed.zip"
filename = os.path.join(os.getcwd(), "brain_ct_data_fixed.zip")
tf.keras.utils.get_file(filename, url)
# Unzip dataset
with zipfile.ZipFile("brain_ct_data_fixed.zip", "r") as z_fp:
z_fp.extractall(".")
NORMAL_PATH = '/content/brain_ct_data_fixed/Normal'
STROKE_PATH = '/content/brain_ct_data_fixed/Stroke'
Before going deeper into data loading it can be interesting to give a look to a single CT slice.
import imageio.v2 as imageio
import matplotlib.pyplot as plt
image = imageio.imread(f'{STROKE_PATH}/67 (15).jpg')
plt.imshow(image, cmap="gray")
<matplotlib.image.AxesImage at 0x7fa302346580>
As it is possible to see, the image presents some artifacts that may hinder the CNN training process. Vicente Rodríguez provided a nice example of CT image denoising that lead to the creation of the following remove_noise function:
from scipy import ndimage
from skimage import morphology
import numpy as np
def remove_noise(image, display=False):
"""Remove slice noise"""
# morphology.dilation creates a segmentation of the image
# If one pixel is between the origin and the edge of a square of size
# 3x3, the pixel belongs to the same class
segmentation = morphology.dilation(image, np.ones((3, 3)))
segmentation[segmentation < 25] = 0
segmentation[segmentation > 25] = 1
labels, label_nb = ndimage.label(segmentation)
label_count = np.bincount(labels.ravel().astype(int))
# The size of label_count is the number of classes/segmentations found.
# The first class is not used since it's the background.
label_count[0] = 0
# A mask with the class with more pixels is created
# since it should represent the brain
mask = labels == label_count.argmax()
# Improve the brain mask
mask = morphology.dilation(mask, np.ones((5, 5)))
mask = ndimage.binary_fill_holes(mask)
mask = morphology.dilation(mask, np.ones((3, 3)))
# Since the pixels in the mask are zeros and ones,
# it is possible to multiple the original image to only keep the brain region
masked_image = mask * image
if display:
plt.figure(figsize=(10, 2.5))
plt.subplot(141)
plt.imshow(image, cmap=plt.cm.bone)
plt.title('Original Image')
plt.axis('off')
plt.subplot(142)
plt.imshow(mask, cmap=plt.cm.bone)
plt.title('Mask')
plt.axis('off')
plt.subplot(143)
plt.imshow(masked_image, cmap=plt.cm.bone)
plt.title('Clean Image')
plt.axis('off')
return masked_image
So, let’s try to remove the background artifacts from the image:
denoised_image = remove_noise(image, display=True)
As expected, the CT artifacts are not present anymore.
It is worth noting despite the CT slices have been correctly sorted and there are no holes in slice sequences anymore, the dataset is still not so straightforward to import since the number of slices per patient is not
always the same. The load_dataset function appears quite complex because it has to execute in sequence multiple steps to load and pre-process the entire image dataset:
count_slices: counts the number of slices per patientmerge_slices: denoises (optionally) and merges all patient slices into a single scannormalize_scan: normalizes the scan values to the interval[0, 1]resize_scan: resizes the scan across x, y and z axis to uniform the scan sizes to fixed values
Finally, the returned dataset is a 4D array, i.e., an array of scans (3D images).
import numpy as np
from tqdm import tqdm
def resize_scan(scan):
"""Resize the CT scan to a desired uniform size across all axis"""
# Set the desired depth
desired_depth = 64
desired_width = 128
desired_height = 128
# Get current depth
current_depth = scan.shape[-1]
current_width = scan.shape[0]
current_height = scan.shape[1]
# Compute depth factor
depth = current_depth / desired_depth
width = current_width / desired_width
height = current_height / desired_height
depth_factor = 1 / depth
width_factor = 1 / width
height_factor = 1 / height
# Rotate
scan = ndimage.rotate(scan, 90, reshape=False)
# Resize across z-axis
scan = ndimage.zoom(scan, (width_factor, height_factor, depth_factor), order=1)
return scan
def normalize_scan(scan):
"""Normalize the scan to the interval [0, 1]"""
min = 0
max = 255
scan[scan < min] = min
scan[scan > max] = max
scan = (scan - min) / (max - min)
scan = scan.astype("float32")
return scan
def merge_slices(path, patient_id, slice_count, denoise=False):
"""Merge all the slices for a patient into a scan"""
if denoise:
scan = tuple(remove_noise(imageio.imread(f'{path}/{patient_id} ({slice_id}).jpg')) for slice_id in range(1, slice_count+1))
else:
scan = tuple(imageio.imread(f'{path}/{patient_id} ({slice_id}).jpg') for slice_id in range(1, slice_count+1))
return np.dstack(scan)
def count_slices(path):
"""Analyze the slices path and returns a dictionary with the slices count associated to each patient"""
slice_dict = {}
for dirname, _, filenames in os.walk(path):
for filename in filenames:
patient_id = int(filename.split()[0])
if patient_id not in slice_dict:
slice_dict[patient_id] = 1
else:
slice_dict[patient_id] = slice_dict[patient_id] + 1
return slice_dict
def collect_scan(path, patient_id, slice_count):
"""Collect a scan for a patient id"""
# Get a single CT scan by merging all the slices from a single patient
# Before getting merged the slices are also denoised
scan = merge_slices(path, patient_id, slice_count, denoise=True)
# Normalize the CT scan to the interval [0, 1]
scan = normalize_scan(scan)
# Resize the CT scan to uniform the size
scan = resize_scan(scan)
return scan
def load_dataset(path):
"""Return the scans dataset as a 4D array"""
# Get a dictionary with patient IDs and slice count per patient
slices_dict = count_slices(path)
# Collect scans for each patient id
dataset = np.array([collect_scan(path, patient_id, slice_count) for patient_id, slice_count in tqdm(slices_dict.items())])
return dataset
Both the normal and stroke datasets are imported from the respective paths. Since the process can take some minutes the tqdm library can help to check the progress in realtime.
normal_dataset = load_dataset(path=NORMAL_PATH)
stroke_dataset = load_dataset(path=STROKE_PATH)
100%|██████████| 51/51 [02:55<00:00, 3.44s/it]
100%|██████████| 31/31 [01:41<00:00, 3.27s/it]
normal_dataset.shape, stroke_dataset.shape
((51, 128, 128, 64), (31, 128, 128, 64))
The normal and stroke datasets are represented by rank-3 tensors of shape (samples, height, width, depth). There are 51 normal and 31 stroke CT scans so the dataset is quite unbalanced.
The function plot_slices_from_dataset can be used to plot an entire CT scan from the loaded dataset.
def plot_scan_from_dataset(num_rows, num_columns, width, height, data, title):
"""Plot a scan from dataset"""
data = np.transpose(data)
data = np.reshape(data, (num_rows, num_columns, width, height))
rows_data, columns_data = data.shape[0], data.shape[1]
heights = [slc[0].shape[0] for slc in data]
widths = [slc.shape[1] for slc in data[0]]
fig_width = 12.0
fig_height = fig_width * sum(heights) / sum(widths)
f, axarr = plt.subplots(
rows_data,
columns_data,
figsize=(fig_width, fig_height),
gridspec_kw={"height_ratios": heights},
)
f.suptitle(title, y=1.1)
for i in range(rows_data):
for j in range(columns_data):
axarr[i, j].imshow(data[i][j], cmap="gray")
axarr[i, j].axis("off")
plt.subplots_adjust(wspace=0, hspace=0, left=0, right=1, bottom=0, top=1)
plt.show()
The first scan from both the normal and stroke datasets is shown hereafter.
plot_scan_from_dataset(4, 16, 128, 128, normal_dataset[0, :, :, :], "Normal CT scan")
plot_scan_from_dataset(4, 16, 128, 128, stroke_dataset[0, :, :, :], "Stroke CT scan")
Both the datasets are now splitted and merged into training and validation datasets with a ratio of 70% and 30%.
# For the CT scans having presence of stroke assign 1 otherwise 0.
normal_labels = np.array([0 for _ in range(len(normal_dataset))])
stroke_labels = np.array([1 for _ in range(len(stroke_dataset))])
# Split data in the ratio 70%-30% for training and validation.
import math
VALIDATION_SPLIT = 0.7
normal_train_len = math.ceil(VALIDATION_SPLIT*len(normal_labels))
stroke_train_len = math.ceil(VALIDATION_SPLIT*len(stroke_labels))
x_train = np.concatenate((normal_dataset[:normal_train_len], stroke_dataset[:stroke_train_len]), axis=0)
y_train = np.concatenate((normal_labels[:normal_train_len], stroke_labels[:stroke_train_len]), axis=0)
x_val = np.concatenate((normal_dataset[normal_train_len:], stroke_dataset[stroke_train_len:]), axis=0)
y_val = np.concatenate((normal_labels[normal_train_len:], stroke_labels[stroke_train_len:]), axis=0)
print(f"Training samples")
print(f"Normal: {normal_train_len}")
print(f"Stroke: {stroke_train_len}")
print(f"Total: {x_train.shape[0]}")
print()
print(f"Validation samples")
print(f"Normal: {len(normal_dataset) - normal_train_len}")
print(f"Stroke: {len(stroke_dataset) - stroke_train_len}")
print(f"Total: {x_val.shape[0]}")
Training samples
Normal: 36
Stroke: 22
Total: 58
Validation samples
Normal: 15
Stroke: 9
Total: 24
Dataset augmentation
A machine learning model performs better and is more accurate when the dataset is rich and sufficient. Deep learning in general, but particularly in medical imaging, requires a large amount of training data in order to obtain good performance and avoid overfitting. To meet these challenges, increasing the quantity of training data is a common solution. Data augmentation is a common approach to enhance the performance and the results of machine learning models. It allows a small dataset to be rebalanced or enriched for any reason (time-consuming manual annotations, lack of accessible data…). The augmentation techniques must make sense with respect to the type of analysis desired and therefore positively influence the performance of the model during the learning phase: by applying a large number of augmentations, the performance will not necessarily be better. There are several types of transformations for medical images, but few examples which can be seen as good starting point for CT scans are provided in the following.
Rotation
This transformation consists of rotating the original image according to a desired angle. In medical image analysis, this represents a common augmentation technique. In this case the scan is rotated around z-axis by a random angle in the interval [-45, 45] degrees.
rotation_layer = tf.keras.layers.RandomRotation(factor=(-0.125, 0.125), fill_mode='constant', fill_value=0)
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, rotation_layer(x_train[0, :, :, :]), "Rotated CT Scan")
Flip
The image flips are performed along an axis of symmetry. For medical image enhancement, they can be performed vertically as well as horizontally, because images can be acquired in supine or prone position, and contain anatomical variations (e.g., situs inversus). An organ, whatever its location in the body, will always be the same organ.
flipping_layer = tf.keras.layers.RandomFlip(mode='vertical')
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, flipping_layer(x_train[0, :, :, :]), "Flipped CT Scan")
Shift
This transformation can be performed along the x and/or y axis randomly. The transformed image keeps the same size and orientation as the original image, but is moved in the applied direction. The added pixels are filled with zeros.
shifting_layer = tf.keras.layers.RandomTranslation(height_factor=0.2, width_factor=0.2, fill_mode='constant', fill_value=0)
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, shifting_layer(x_train[0, :, :, :]), "Shifted CT Scan")
Zoom
A zoom augmentation randomly zooms the image in or out. The zoomed image keeps the same size and orientation as the original image.
zoom_layer = tf.keras.layers.RandomZoom(height_factor=0.15, fill_mode='constant', fill_value=0)
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, zoom_layer(x_train[0, :, :, :]), "Zoomed CT Scan")
Shear
Shearing is an affine transformation that consists of shifting in opposite directions the top and bottom of the image (horizontal shearing) or the right and left of the image (vertical shearing). Unlike the previous methods, the image is distorted. Shear augmentation is not available in tensorflow so the keras_cv package must be installed.
!pip install keras_cv
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting keras_cv
Downloading keras_cv-0.4.2-py3-none-any.whl (634 kB)
[2K [90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━[0m [32m634.9/634.9 kB[0m [31m13.2 MB/s[0m eta [36m0:00:00[0m
[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.9/dist-packages (from keras_cv) (23.1)
Requirement already satisfied: absl-py in /usr/local/lib/python3.9/dist-packages (from keras_cv) (1.4.0)
Requirement already satisfied: tensorflow-datasets in /usr/local/lib/python3.9/dist-packages (from keras_cv) (4.8.3)
Requirement already satisfied: regex in /usr/local/lib/python3.9/dist-packages (from keras_cv) (2022.10.31)
Requirement already satisfied: promise in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (2.3)
Requirement already satisfied: tensorflow-metadata in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (1.13.1)
Requirement already satisfied: tqdm in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (4.65.0)
Requirement already satisfied: protobuf>=3.12.2 in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (3.20.3)
Requirement already satisfied: toml in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (0.10.2)
Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (2.27.1)
Requirement already satisfied: click in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (8.1.3)
Requirement already satisfied: etils[enp,epath]>=0.9.0 in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (1.2.0)
Requirement already satisfied: termcolor in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (2.2.0)
Requirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (1.22.4)
Requirement already satisfied: wrapt in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (1.14.1)
Requirement already satisfied: psutil in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (5.9.5)
Requirement already satisfied: dm-tree in /usr/local/lib/python3.9/dist-packages (from tensorflow-datasets->keras_cv) (0.1.8)
Requirement already satisfied: importlib_resources in /usr/local/lib/python3.9/dist-packages (from etils[enp,epath]>=0.9.0->tensorflow-datasets->keras_cv) (5.12.0)
Requirement already satisfied: zipp in /usr/local/lib/python3.9/dist-packages (from etils[enp,epath]>=0.9.0->tensorflow-datasets->keras_cv) (3.15.0)
Requirement already satisfied: typing_extensions in /usr/local/lib/python3.9/dist-packages (from etils[enp,epath]>=0.9.0->tensorflow-datasets->keras_cv) (4.5.0)
Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests>=2.19.0->tensorflow-datasets->keras_cv) (3.4)
Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests>=2.19.0->tensorflow-datasets->keras_cv) (2022.12.7)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests>=2.19.0->tensorflow-datasets->keras_cv) (1.26.15)
Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests>=2.19.0->tensorflow-datasets->keras_cv) (2.0.12)
Requirement already satisfied: six in /usr/local/lib/python3.9/dist-packages (from promise->tensorflow-datasets->keras_cv) (1.16.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.9/dist-packages (from tensorflow-metadata->tensorflow-datasets->keras_cv) (1.59.0)
Installing collected packages: keras_cv
Successfully installed keras_cv-0.4.2
import keras_cv
shear_layer = keras_cv.layers.RandomShear(x_factor=(0, 0.3), y_factor=(0, 0.3), interpolation="bilinear", fill_mode="nearest", fill_value=0.0)
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, shear_layer(x_train[0, :, :, :]), "Sheared CT Scan")
You do not have Waymo Open Dataset installed, so KerasCV Waymo metrics are not available.
Brightness
The higher the value of the brighteness, the lighter is the image. In order to increase the size of the data set in medical imaging, brightness variations belonging to the interval [-0.1; 0.1] are randomly applied.
brighteness_layer = tf.keras.layers.RandomBrightness(factor=0.1, value_range=[0.0, 1.0])
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, brighteness_layer(x_train[0, :, :, :]), "Brightened CT Scan")
Contrast
The contrast of an image is increased when the darker pixels are darkened and the lighter pixels are lightened: a contrasted image will therefore contain a greater quantity of black and white. The contrast increase is clearly visible on image histogram, because the gap between the brightest and the darkest pixels is greater, i.e., the histogram is more spread out.
contrast_layer = tf.keras.layers.RandomContrast(factor=(0, 1.2))
plot_scan_from_dataset(4, 16, 128, 128, x_train[0, :, :, :], "Original CT Scan")
plot_scan_from_dataset(4, 16, 128, 128, contrast_layer(x_train[0, :, :, :]), "Contrasted CT Scan")
The training and validation data loaders must be defined. In this case, data augmentation is not applied through the data loader but directly on the CNN by adding the related augmentation layers.
# Set TensorFlow random seed
tf.random.set_seed(42)
# Define data loaders
training_loader = tf.data.Dataset.from_tensor_slices((x_train, y_train))
validation_loader = tf.data.Dataset.from_tensor_slices((x_val, y_val))
# Define batch size
batch_size = 2
# Training dataset
training_dataset = (
training_loader.shuffle(len(x_train))
.batch(batch_size)
.prefetch(2)
)
# Validation dataset
validation_dataset = (
validation_loader.shuffle(len(x_val))
.batch(batch_size)
.prefetch(2)
)
Model definition
The architecture of the 3D CNN is the same used here, but, as already said, the CT scans are optionally augmented by passing them through some augmentation layers which have been directly embedded into the model. A reshape layer has also been added since the data is stored in rank-3 tensors of shape (samples, height, width, depth), a dimension of size 1 at axis 4 is needed in order to be able to perform 3D convolutions on the data. The additional dimension is needed to take into account the number of image channel which in this case is just 1.
from tensorflow import keras
from tensorflow.keras import layers
# Default arguments
WIDTH=128
HEIGHT=128
DEPTH=64
INITIAL_LEARNING_RATE=0.0001
DECAY_STEPS=100000
DECAY_RATE=0.96
# Performance metrics
METRICS=[
keras.metrics.TruePositives(name='tp'),
keras.metrics.FalsePositives(name='fp'),
keras.metrics.TrueNegatives(name='tn'),
keras.metrics.FalseNegatives(name='fn'),
keras.metrics.BinaryAccuracy(name='accuracy'),
keras.metrics.Precision(name='precision'),
keras.metrics.Recall(name='recall'),
keras.metrics.AUC(name='auc'),
keras.metrics.AUC(name='prc', curve='PR'), # precision-recall curve
]
def build_model(width=WIDTH,
height=HEIGHT,
depth=DEPTH,
initial_learning_rate=INITIAL_LEARNING_RATE,
decay_steps=DECAY_STEPS,
decay_rate=DECAY_RATE,
metrics=METRICS,
augmentation=False,
rotation=False,
flip=False,
shift=False,
zoom=False,
shear=False,
brightness=False,
contrast=False):
"""Build a 3D convolutional neural network model with augmentation layers"""
# Define the model
model = keras.Sequential()
model.add(keras.Input((width, height, depth)))
# (Optionally) Add augmentation layers
if augmentation:
if rotation:
model.add(layers.RandomRotation(factor=(-0.125, 0.125), fill_mode='constant', fill_value=0))
if flip:
model.add(layers.RandomFlip(mode='vertical'))
if shift:
model.add(layers.RandomTranslation(height_factor=0.2, width_factor=0.2, fill_mode='constant', fill_value=0))
if zoom:
model.add(layers.RandomZoom(height_factor=0.15, fill_mode='constant', fill_value=0))
if shear:
model.add(keras_cv.layers.RandomShear(x_factor=(0, 0.3), y_factor=(0, 0.3), interpolation="bilinear", fill_mode="nearest", fill_value=0.0))
if brightness:
model.add(layers.RandomBrightness(factor=0.1, value_range=[0.0, 1.0]))
if contrast:
model.add(layers.RandomContrast(factor=(0, 1.2)))
# Add a dimension to perform 3D convolutions
model.add(layers.Reshape(target_shape=(width, height, depth, 1)))
model.add(layers.Conv3D(filters=64, kernel_size=3, activation="relu"))
model.add(layers.MaxPool3D(pool_size=2))
model.add(layers.BatchNormalization())
model.add(layers.Conv3D(filters=64, kernel_size=3, activation="relu"))
model.add(layers.MaxPool3D(pool_size=2))
model.add(layers.BatchNormalization())
model.add(layers.Conv3D(filters=128, kernel_size=3, activation="relu"))
model.add(layers.MaxPool3D(pool_size=2))
model.add(layers.BatchNormalization())
model.add(layers.Conv3D(filters=256, kernel_size=3, activation="relu"))
model.add(layers.MaxPool3D(pool_size=2))
model.add(layers.BatchNormalization())
model.add(layers.GlobalAveragePooling3D())
model.add(layers.Dense(units=512, activation="relu"))
model.add(layers.Dropout(0.3))
model.add(layers.Dense(units=1, activation="sigmoid"))
# Define the optimizer
lr_schedule = keras.optimizers.schedules.ExponentialDecay(
initial_learning_rate, decay_steps=decay_steps, decay_rate=decay_rate, staircase=True
)
# Compile the model
model.compile(
loss="binary_crossentropy",
optimizer=keras.optimizers.Adam(learning_rate=lr_schedule),
metrics=metrics,
)
return model
# Build the model with default parameters
model = build_model()
# Print the model summary
model.summary()
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
reshape (Reshape) (None, 128, 128, 64, 1) 0
conv3d (Conv3D) (None, 126, 126, 62, 64) 1792
max_pooling3d (MaxPooling3D (None, 63, 63, 31, 64) 0
)
batch_normalization (BatchN (None, 63, 63, 31, 64) 256
ormalization)
conv3d_1 (Conv3D) (None, 61, 61, 29, 64) 110656
max_pooling3d_1 (MaxPooling (None, 30, 30, 14, 64) 0
3D)
batch_normalization_1 (Batc (None, 30, 30, 14, 64) 256
hNormalization)
conv3d_2 (Conv3D) (None, 28, 28, 12, 128) 221312
max_pooling3d_2 (MaxPooling (None, 14, 14, 6, 128) 0
3D)
batch_normalization_2 (Batc (None, 14, 14, 6, 128) 512
hNormalization)
conv3d_3 (Conv3D) (None, 12, 12, 4, 256) 884992
max_pooling3d_3 (MaxPooling (None, 6, 6, 2, 256) 0
3D)
batch_normalization_3 (Batc (None, 6, 6, 2, 256) 1024
hNormalization)
global_average_pooling3d (G (None, 256) 0
lobalAveragePooling3D)
dense (Dense) (None, 512) 131584
dropout (Dropout) (None, 512) 0
dense_1 (Dense) (None, 1) 513
=================================================================
Total params: 1,352,897
Trainable params: 1,351,873
Non-trainable params: 1,024
_________________________________________________________________
Model training
The proposed model will be trained by default for 150 epochs in 4 different conditions:
- Absent augmentation: all augmentation layers disabled
- Basic augmentation: brightness and contrast layers enabled
- Intermediate augmentation: brightness, contrast, rotation, flip and shift layers enabled
- Advanced augmentation: all augmentation layers enabled
It is worth noting a Checkpoint callback is also defined to automatically save the model in h5 format based on the validation Receiver Operating Characteristics Area Under Curve (ROC AUC) value. Please note the ROC AUC is preferred to the standard classification accuracy since the dataset is not balanced.
# Default epochs number
EPOCHS=150
# Callback
CHECKPOINT_CB = keras.callbacks.ModelCheckpoint(
"ct-scan-brain-stroke-detection-{epoch:03d}-{val_auc:.4f}.h5",
save_best_only=True,
monitor='val_auc',
mode='max'
)
# Model training function
def train_model(model, training_dataset, validation_dataset, epochs=EPOCHS, callbacks=[CHECKPOINT_CB]):
"""Train a model doing validation at the end of each epoch"""
history = model.fit(
training_dataset,
validation_data=validation_dataset,
epochs=epochs,
shuffle=True,
verbose=1,
callbacks=callbacks
)
return history
An empty dictionary to store model metrics is also created to store all the metrics.
performance = {}
Absent augmentation
In this case the data augmentation is completely disabled. The model will be trained by using only the CT scans already available in the training dataset.
model = build_model()
performance["absent"] = train_model(model, training_dataset, validation_dataset)
Epoch 1/150
29/29 [==============================] - 27s 197ms/step - loss: 0.7002 - tp: 6.0000 - fp: 14.0000 - tn: 22.0000 - fn: 16.0000 - accuracy: 0.4828 - precision: 0.3000 - recall: 0.2727 - auc: 0.4236 - prc: 0.3796 - val_loss: 0.6891 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6741 - val_prc: 0.5665
Epoch 2/150
29/29 [==============================] - 5s 170ms/step - loss: 0.6772 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.5852 - prc: 0.4299 - val_loss: 0.6758 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6556 - val_prc: 0.6161
Epoch 3/150
29/29 [==============================] - 5s 172ms/step - loss: 0.6412 - tp: 13.0000 - fp: 8.0000 - tn: 28.0000 - fn: 9.0000 - accuracy: 0.7069 - precision: 0.6190 - recall: 0.5909 - auc: 0.7184 - prc: 0.6360 - val_loss: 0.9218 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6111 - val_prc: 0.4476
Epoch 4/150
29/29 [==============================] - 5s 171ms/step - loss: 0.6143 - tp: 10.0000 - fp: 5.0000 - tn: 31.0000 - fn: 12.0000 - accuracy: 0.7069 - precision: 0.6667 - recall: 0.4545 - auc: 0.7279 - prc: 0.6874 - val_loss: 0.7125 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6259 - val_prc: 0.5567
Epoch 5/150
29/29 [==============================] - 5s 175ms/step - loss: 0.6074 - tp: 10.0000 - fp: 3.0000 - tn: 33.0000 - fn: 12.0000 - accuracy: 0.7414 - precision: 0.7692 - recall: 0.4545 - auc: 0.7330 - prc: 0.5813 - val_loss: 0.7482 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6519 - val_prc: 0.5625
Epoch 6/150
29/29 [==============================] - 5s 173ms/step - loss: 0.6351 - tp: 8.0000 - fp: 7.0000 - tn: 29.0000 - fn: 14.0000 - accuracy: 0.6379 - precision: 0.5333 - recall: 0.3636 - auc: 0.6938 - prc: 0.5982 - val_loss: 1.2574 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6481 - val_prc: 0.6029
Epoch 7/150
29/29 [==============================] - 5s 173ms/step - loss: 0.6018 - tp: 10.0000 - fp: 7.0000 - tn: 29.0000 - fn: 12.0000 - accuracy: 0.6724 - precision: 0.5882 - recall: 0.4545 - auc: 0.7551 - prc: 0.5616 - val_loss: 0.8819 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6556 - val_prc: 0.6027
Epoch 8/150
29/29 [==============================] - 5s 174ms/step - loss: 0.5746 - tp: 14.0000 - fp: 7.0000 - tn: 29.0000 - fn: 8.0000 - accuracy: 0.7414 - precision: 0.6667 - recall: 0.6364 - auc: 0.7696 - prc: 0.6991 - val_loss: 1.0019 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5889 - val_prc: 0.5081
Epoch 9/150
29/29 [==============================] - 5s 174ms/step - loss: 0.5749 - tp: 12.0000 - fp: 3.0000 - tn: 33.0000 - fn: 10.0000 - accuracy: 0.7759 - precision: 0.8000 - recall: 0.5455 - auc: 0.7254 - prc: 0.6337 - val_loss: 1.4884 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6111 - val_prc: 0.5376
Epoch 10/150
29/29 [==============================] - 5s 187ms/step - loss: 0.5709 - tp: 10.0000 - fp: 7.0000 - tn: 29.0000 - fn: 12.0000 - accuracy: 0.6724 - precision: 0.5882 - recall: 0.4545 - auc: 0.7557 - prc: 0.6680 - val_loss: 1.6774 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6593 - val_prc: 0.6106
Epoch 11/150
29/29 [==============================] - 5s 176ms/step - loss: 0.5601 - tp: 12.0000 - fp: 7.0000 - tn: 29.0000 - fn: 10.0000 - accuracy: 0.7069 - precision: 0.6316 - recall: 0.5455 - auc: 0.7670 - prc: 0.6901 - val_loss: 2.4892 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6519 - val_prc: 0.4787
Epoch 12/150
29/29 [==============================] - 5s 178ms/step - loss: 0.5151 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8396 - prc: 0.7432 - val_loss: 2.5274 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6222 - val_prc: 0.4381
Epoch 13/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4865 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8396 - prc: 0.8283 - val_loss: 3.3881 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4667 - val_prc: 0.3570
Epoch 14/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4484 - tp: 15.0000 - fp: 2.0000 - tn: 34.0000 - fn: 7.0000 - accuracy: 0.8448 - precision: 0.8824 - recall: 0.6818 - auc: 0.9198 - prc: 0.8888 - val_loss: 1.4274 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5889 - val_prc: 0.5541
Epoch 15/150
29/29 [==============================] - 6s 201ms/step - loss: 0.4467 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.8946 - prc: 0.8335 - val_loss: 2.2831 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5889 - val_prc: 0.5586
Epoch 16/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3943 - tp: 16.0000 - fp: 2.0000 - tn: 34.0000 - fn: 6.0000 - accuracy: 0.8621 - precision: 0.8889 - recall: 0.7273 - auc: 0.9192 - prc: 0.8970 - val_loss: 5.1814 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.3750
Epoch 17/150
29/29 [==============================] - 6s 201ms/step - loss: 0.3981 - tp: 18.0000 - fp: 4.0000 - tn: 32.0000 - fn: 4.0000 - accuracy: 0.8621 - precision: 0.8182 - recall: 0.8182 - auc: 0.9072 - prc: 0.8860 - val_loss: 4.0833 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.3750
Epoch 18/150
29/29 [==============================] - 5s 177ms/step - loss: 0.2982 - tp: 21.0000 - fp: 5.0000 - tn: 31.0000 - fn: 1.0000 - accuracy: 0.8966 - precision: 0.8077 - recall: 0.9545 - auc: 0.9760 - prc: 0.9722 - val_loss: 1.5026 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5741 - val_prc: 0.5433
Epoch 19/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4235 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.8832 - prc: 0.7512 - val_loss: 2.1605 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4963 - val_prc: 0.4582
Epoch 20/150
29/29 [==============================] - 5s 176ms/step - loss: 0.4055 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.9129 - prc: 0.8750 - val_loss: 1.7596 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6481 - val_prc: 0.5424
Epoch 21/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3645 - tp: 16.0000 - fp: 2.0000 - tn: 34.0000 - fn: 6.0000 - accuracy: 0.8621 - precision: 0.8889 - recall: 0.7273 - auc: 0.9280 - prc: 0.8974 - val_loss: 1.9915 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6370 - val_prc: 0.5410
Epoch 22/150
29/29 [==============================] - 5s 176ms/step - loss: 0.2712 - tp: 19.0000 - fp: 3.0000 - tn: 33.0000 - fn: 3.0000 - accuracy: 0.8966 - precision: 0.8636 - recall: 0.8636 - auc: 0.9672 - prc: 0.9585 - val_loss: 0.8103 - val_tp: 4.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 5.0000 - val_accuracy: 0.4583 - val_precision: 0.3333 - val_recall: 0.4444 - val_auc: 0.5926 - val_prc: 0.5532
Epoch 23/150
29/29 [==============================] - 5s 175ms/step - loss: 0.3840 - tp: 15.0000 - fp: 4.0000 - tn: 32.0000 - fn: 7.0000 - accuracy: 0.8103 - precision: 0.7895 - recall: 0.6818 - auc: 0.8832 - prc: 0.8661 - val_loss: 1.5774 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6185 - val_prc: 0.5903
Epoch 24/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3379 - tp: 19.0000 - fp: 6.0000 - tn: 30.0000 - fn: 3.0000 - accuracy: 0.8448 - precision: 0.7600 - recall: 0.8636 - auc: 0.9501 - prc: 0.9453 - val_loss: 0.8694 - val_tp: 6.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 3.0000 - val_accuracy: 0.5833 - val_precision: 0.4615 - val_recall: 0.6667 - val_auc: 0.6074 - val_prc: 0.5338
Epoch 25/150
29/29 [==============================] - 5s 175ms/step - loss: 0.2800 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9811 - prc: 0.9720 - val_loss: 2.4292 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6370 - val_prc: 0.4767
Epoch 26/150
29/29 [==============================] - 6s 203ms/step - loss: 0.4072 - tp: 16.0000 - fp: 7.0000 - tn: 29.0000 - fn: 6.0000 - accuracy: 0.7759 - precision: 0.6957 - recall: 0.7273 - auc: 0.8876 - prc: 0.8567 - val_loss: 1.6198 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.6815 - val_prc: 0.4556
Epoch 27/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3483 - tp: 15.0000 - fp: 1.0000 - tn: 35.0000 - fn: 7.0000 - accuracy: 0.8621 - precision: 0.9375 - recall: 0.6818 - auc: 0.9337 - prc: 0.9232 - val_loss: 2.2016 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6963 - val_prc: 0.6890
Epoch 28/150
29/29 [==============================] - 5s 176ms/step - loss: 0.2698 - tp: 17.0000 - fp: 2.0000 - tn: 34.0000 - fn: 5.0000 - accuracy: 0.8793 - precision: 0.8947 - recall: 0.7727 - auc: 0.9747 - prc: 0.9634 - val_loss: 0.8487 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.6444 - val_prc: 0.5897
Epoch 29/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4407 - tp: 15.0000 - fp: 6.0000 - tn: 30.0000 - fn: 7.0000 - accuracy: 0.7759 - precision: 0.7143 - recall: 0.6818 - auc: 0.8611 - prc: 0.8201 - val_loss: 0.8850 - val_tp: 3.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 6.0000 - val_accuracy: 0.7083 - val_precision: 0.7500 - val_recall: 0.3333 - val_auc: 0.6741 - val_prc: 0.5209
Epoch 30/150
29/29 [==============================] - 5s 176ms/step - loss: 0.2629 - tp: 16.0000 - fp: 1.0000 - tn: 35.0000 - fn: 6.0000 - accuracy: 0.8793 - precision: 0.9412 - recall: 0.7273 - auc: 0.9760 - prc: 0.9617 - val_loss: 1.5557 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.6852 - val_prc: 0.5492
Epoch 31/150
29/29 [==============================] - 6s 201ms/step - loss: 0.1817 - tp: 21.0000 - fp: 3.0000 - tn: 33.0000 - fn: 1.0000 - accuracy: 0.9310 - precision: 0.8750 - recall: 0.9545 - auc: 0.9931 - prc: 0.9889 - val_loss: 1.0616 - val_tp: 6.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 3.0000 - val_accuracy: 0.5000 - val_precision: 0.4000 - val_recall: 0.6667 - val_auc: 0.6778 - val_prc: 0.5999
Epoch 32/150
29/29 [==============================] - 5s 178ms/step - loss: 0.2270 - tp: 18.0000 - fp: 2.0000 - tn: 34.0000 - fn: 4.0000 - accuracy: 0.8966 - precision: 0.9000 - recall: 0.8182 - auc: 0.9729 - prc: 0.9623 - val_loss: 1.7977 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6148 - val_prc: 0.4962
Epoch 33/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2288 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9874 - prc: 0.9798 - val_loss: 1.0614 - val_tp: 7.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 2.0000 - val_accuracy: 0.5417 - val_precision: 0.4375 - val_recall: 0.7778 - val_auc: 0.6222 - val_prc: 0.5203
Epoch 34/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2219 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9785 - prc: 0.9716 - val_loss: 0.8000 - val_tp: 5.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 4.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.5556 - val_auc: 0.6667 - val_prc: 0.5838
Epoch 35/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3234 - tp: 15.0000 - fp: 2.0000 - tn: 34.0000 - fn: 7.0000 - accuracy: 0.8448 - precision: 0.8824 - recall: 0.6818 - auc: 0.9306 - prc: 0.9080 - val_loss: 2.3090 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5741 - val_prc: 0.4023
Epoch 36/150
29/29 [==============================] - 5s 181ms/step - loss: 0.2608 - tp: 19.0000 - fp: 2.0000 - tn: 34.0000 - fn: 3.0000 - accuracy: 0.9138 - precision: 0.9048 - recall: 0.8636 - auc: 0.9697 - prc: 0.9545 - val_loss: 0.9518 - val_tp: 6.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 3.0000 - val_accuracy: 0.5833 - val_precision: 0.4615 - val_recall: 0.6667 - val_auc: 0.7037 - val_prc: 0.6025
Epoch 37/150
29/29 [==============================] - 5s 176ms/step - loss: 0.2390 - tp: 18.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 4.0000 - accuracy: 0.9310 - precision: 1.0000 - recall: 0.8182 - auc: 0.9634 - prc: 0.9554 - val_loss: 0.8774 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.5630 - val_prc: 0.5661
Epoch 38/150
29/29 [==============================] - 6s 199ms/step - loss: 0.0959 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.9335 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.5704 - val_prc: 0.5011
Epoch 39/150
29/29 [==============================] - 5s 175ms/step - loss: 0.1951 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9962 - prc: 0.9936 - val_loss: 2.5183 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5889 - val_prc: 0.3990
Epoch 40/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1823 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9848 - prc: 0.9738 - val_loss: 1.6855 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.6037 - val_prc: 0.6092
Epoch 41/150
29/29 [==============================] - 5s 175ms/step - loss: 0.2639 - tp: 18.0000 - fp: 2.0000 - tn: 34.0000 - fn: 4.0000 - accuracy: 0.8966 - precision: 0.9000 - recall: 0.8182 - auc: 0.9653 - prc: 0.9454 - val_loss: 1.5368 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.6741 - val_prc: 0.5285
Epoch 42/150
29/29 [==============================] - 6s 199ms/step - loss: 0.2371 - tp: 18.0000 - fp: 2.0000 - tn: 34.0000 - fn: 4.0000 - accuracy: 0.8966 - precision: 0.9000 - recall: 0.8182 - auc: 0.9823 - prc: 0.9715 - val_loss: 1.2670 - val_tp: 8.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 1.0000 - val_accuracy: 0.6667 - val_precision: 0.5333 - val_recall: 0.8889 - val_auc: 0.6852 - val_prc: 0.4862
Epoch 43/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1463 - tp: 21.0000 - fp: 3.0000 - tn: 33.0000 - fn: 1.0000 - accuracy: 0.9310 - precision: 0.8750 - recall: 0.9545 - auc: 0.9937 - prc: 0.9914 - val_loss: 4.2052 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5519 - val_prc: 0.4005
Epoch 44/150
29/29 [==============================] - 5s 176ms/step - loss: 0.2017 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9912 - prc: 0.9866 - val_loss: 1.6621 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.6778 - val_prc: 0.6399
Epoch 45/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1629 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9899 - prc: 0.9856 - val_loss: 0.9936 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6630 - val_prc: 0.5719
Epoch 46/150
29/29 [==============================] - 5s 177ms/step - loss: 0.2487 - tp: 17.0000 - fp: 1.0000 - tn: 35.0000 - fn: 5.0000 - accuracy: 0.8966 - precision: 0.9444 - recall: 0.7727 - auc: 0.9697 - prc: 0.9577 - val_loss: 0.9438 - val_tp: 4.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 5.0000 - val_accuracy: 0.5417 - val_precision: 0.4000 - val_recall: 0.4444 - val_auc: 0.6407 - val_prc: 0.5744
Epoch 47/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1986 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9899 - prc: 0.9856 - val_loss: 0.9540 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.6148 - val_prc: 0.5791
Epoch 48/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1564 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9975 - prc: 0.9961 - val_loss: 1.5473 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.6926 - val_prc: 0.6765
Epoch 49/150
29/29 [==============================] - 6s 200ms/step - loss: 0.1103 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6924 - val_tp: 7.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 2.0000 - val_accuracy: 0.4583 - val_precision: 0.3889 - val_recall: 0.7778 - val_auc: 0.6074 - val_prc: 0.4373
Epoch 50/150
29/29 [==============================] - 5s 176ms/step - loss: 0.2040 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9747 - prc: 0.9741 - val_loss: 1.6458 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.6000 - val_prc: 0.4968
Epoch 51/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1739 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9842 - prc: 0.9797 - val_loss: 2.3496 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6444 - val_prc: 0.4245
Epoch 52/150
29/29 [==============================] - 5s 180ms/step - loss: 0.1342 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 0.9955 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.7296 - val_prc: 0.5711
Epoch 53/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0941 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.0994 - val_tp: 6.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 3.0000 - val_accuracy: 0.5417 - val_precision: 0.4286 - val_recall: 0.6667 - val_auc: 0.6667 - val_prc: 0.5371
Epoch 54/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1554 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9949 - prc: 0.9913 - val_loss: 0.9879 - val_tp: 5.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 4.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.5556 - val_auc: 0.7074 - val_prc: 0.5396
Epoch 55/150
29/29 [==============================] - 5s 175ms/step - loss: 0.2241 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9665 - prc: 0.9654 - val_loss: 1.3689 - val_tp: 3.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 6.0000 - val_accuracy: 0.7083 - val_precision: 0.7500 - val_recall: 0.3333 - val_auc: 0.6667 - val_prc: 0.6136
Epoch 56/150
29/29 [==============================] - 6s 199ms/step - loss: 0.1488 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9912 - prc: 0.9871 - val_loss: 1.0276 - val_tp: 5.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 4.0000 - val_accuracy: 0.5417 - val_precision: 0.4167 - val_recall: 0.5556 - val_auc: 0.7074 - val_prc: 0.5311
Epoch 57/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1302 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9924 - prc: 0.9882 - val_loss: 1.4677 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.6667 - val_prc: 0.4548
Epoch 58/150
29/29 [==============================] - 6s 199ms/step - loss: 0.0934 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9975 - prc: 0.9959 - val_loss: 1.1227 - val_tp: 5.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 4.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.5556 - val_auc: 0.6519 - val_prc: 0.4788
Epoch 59/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0896 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.2691 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6704 - val_prc: 0.5122
Epoch 60/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0990 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.2702 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6593 - val_prc: 0.4669
Epoch 61/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1886 - tp: 17.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 5.0000 - accuracy: 0.9138 - precision: 1.0000 - recall: 0.7727 - auc: 0.9886 - prc: 0.9814 - val_loss: 1.4041 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.6037 - val_prc: 0.5516
Epoch 62/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1292 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9912 - prc: 0.9880 - val_loss: 1.7597 - val_tp: 1.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 8.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.1111 - val_auc: 0.5481 - val_prc: 0.4779
Epoch 63/150
29/29 [==============================] - 6s 199ms/step - loss: 0.1297 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9949 - prc: 0.9929 - val_loss: 2.6302 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.6444 - val_prc: 0.6408
Epoch 64/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1330 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9937 - prc: 0.9889 - val_loss: 1.0390 - val_tp: 4.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 5.0000 - val_accuracy: 0.5000 - val_precision: 0.3636 - val_recall: 0.4444 - val_auc: 0.6630 - val_prc: 0.4934
Epoch 65/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1245 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9937 - prc: 0.9914 - val_loss: 1.0608 - val_tp: 5.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 4.0000 - val_accuracy: 0.6667 - val_precision: 0.5556 - val_recall: 0.5556 - val_auc: 0.6481 - val_prc: 0.5704
Epoch 66/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1628 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9716 - prc: 0.9752 - val_loss: 2.2087 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.6000 - val_prc: 0.6069
Epoch 67/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1194 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9962 - prc: 0.9944 - val_loss: 4.2144 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5556 - val_prc: 0.5004
Epoch 68/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0941 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6846 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.6222 - val_prc: 0.6412
Epoch 69/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1476 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9949 - prc: 0.9923 - val_loss: 1.7396 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.6444 - val_prc: 0.5999
Epoch 70/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1227 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9962 - prc: 0.9940 - val_loss: 2.6796 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6815 - val_prc: 0.4732
Epoch 71/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0697 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.4592 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7296 - val_prc: 0.5296
Epoch 72/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1266 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9924 - prc: 0.9901 - val_loss: 3.2876 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6407 - val_prc: 0.4582
Epoch 73/150
29/29 [==============================] - 5s 175ms/step - loss: 0.1239 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9975 - prc: 0.9961 - val_loss: 2.2804 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.6185 - val_prc: 0.4414
Epoch 74/150
29/29 [==============================] - 6s 199ms/step - loss: 0.2016 - tp: 19.0000 - fp: 2.0000 - tn: 34.0000 - fn: 3.0000 - accuracy: 0.9138 - precision: 0.9048 - recall: 0.8636 - auc: 0.9798 - prc: 0.9700 - val_loss: 1.2627 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.6963 - val_prc: 0.6087
Epoch 75/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1060 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.3861 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.6926 - val_prc: 0.6100
Epoch 76/150
29/29 [==============================] - 6s 199ms/step - loss: 0.1422 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9886 - prc: 0.9816 - val_loss: 1.2345 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.6296 - val_prc: 0.5761
Epoch 77/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1297 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9912 - prc: 0.9866 - val_loss: 1.2191 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6556 - val_prc: 0.4480
Epoch 78/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0902 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.1026 - val_tp: 4.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 5.0000 - val_accuracy: 0.5417 - val_precision: 0.4000 - val_recall: 0.4444 - val_auc: 0.6667 - val_prc: 0.5737
Epoch 79/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0901 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.1582 - val_tp: 2.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 7.0000 - val_accuracy: 0.5833 - val_precision: 0.4000 - val_recall: 0.2222 - val_auc: 0.6556 - val_prc: 0.5782
Epoch 80/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0799 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5908 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.6444 - val_prc: 0.4394
Epoch 81/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0732 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.1505 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6667 - val_prc: 0.4678
Epoch 82/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0690 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.0628 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6926 - val_prc: 0.5508
Epoch 83/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0638 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 6.1388 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5667 - val_prc: 0.4091
Epoch 84/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0597 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.2742 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.6519 - val_prc: 0.4380
Epoch 85/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0775 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.1804 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6704 - val_prc: 0.5004
Epoch 86/150
29/29 [==============================] - 5s 175ms/step - loss: 0.0678 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.1592 - val_tp: 2.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 7.0000 - val_accuracy: 0.5000 - val_precision: 0.2857 - val_recall: 0.2222 - val_auc: 0.6407 - val_prc: 0.5148
Epoch 87/150
29/29 [==============================] - 6s 198ms/step - loss: 0.1512 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9798 - prc: 0.9763 - val_loss: 2.1435 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.6296 - val_prc: 0.4175
Epoch 88/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1141 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9949 - prc: 0.9929 - val_loss: 2.9144 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6111 - val_prc: 0.5895
Epoch 89/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1031 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.3662 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.5630 - val_prc: 0.5318
Epoch 90/150
29/29 [==============================] - 6s 200ms/step - loss: 0.2066 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9659 - prc: 0.9595 - val_loss: 1.1912 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.6741 - val_prc: 0.6291
Epoch 91/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1104 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9962 - prc: 0.9944 - val_loss: 1.2353 - val_tp: 7.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 2.0000 - val_accuracy: 0.7083 - val_precision: 0.5833 - val_recall: 0.7778 - val_auc: 0.6370 - val_prc: 0.5101
Epoch 92/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0842 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9975 - prc: 0.9961 - val_loss: 1.3635 - val_tp: 7.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 2.0000 - val_accuracy: 0.6667 - val_precision: 0.5385 - val_recall: 0.7778 - val_auc: 0.6444 - val_prc: 0.4446
Epoch 93/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0366 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3471 - val_tp: 6.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 3.0000 - val_accuracy: 0.5833 - val_precision: 0.4615 - val_recall: 0.6667 - val_auc: 0.6481 - val_prc: 0.4888
Epoch 94/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0423 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.1969 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.6704 - val_prc: 0.5168
Epoch 95/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0497 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.7935 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.5667 - val_prc: 0.5603
Epoch 96/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1108 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9962 - prc: 0.9936 - val_loss: 1.2713 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.6741 - val_prc: 0.5315
Epoch 97/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1410 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9855 - prc: 0.9805 - val_loss: 1.8814 - val_tp: 3.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 6.0000 - val_accuracy: 0.7083 - val_precision: 0.7500 - val_recall: 0.3333 - val_auc: 0.5667 - val_prc: 0.5949
Epoch 98/150
29/29 [==============================] - 5s 181ms/step - loss: 0.1199 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9937 - prc: 0.9895 - val_loss: 1.6763 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6407 - val_prc: 0.4256
Epoch 99/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0804 - tp: 22.0000 - fp: 2.0000 - tn: 34.0000 - fn: 0.0000e+00 - accuracy: 0.9655 - precision: 0.9167 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4800 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.5667 - val_prc: 0.4307
Epoch 100/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1267 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9899 - prc: 0.9838 - val_loss: 1.5902 - val_tp: 2.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 7.0000 - val_accuracy: 0.5833 - val_precision: 0.4000 - val_recall: 0.2222 - val_auc: 0.6074 - val_prc: 0.4193
Epoch 101/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0394 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5032 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.6778 - val_prc: 0.4642
Epoch 102/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0717 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3194 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.6667 - val_prc: 0.4895
Epoch 103/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0620 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9994 - prc: 0.9990 - val_loss: 1.3006 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.6370 - val_prc: 0.4972
Epoch 104/150
29/29 [==============================] - 6s 201ms/step - loss: 0.0364 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.2496 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.6519 - val_prc: 0.5683
Epoch 105/150
29/29 [==============================] - 5s 175ms/step - loss: 0.0381 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5330 - val_tp: 6.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 3.0000 - val_accuracy: 0.5417 - val_precision: 0.4286 - val_recall: 0.6667 - val_auc: 0.6556 - val_prc: 0.4690
Epoch 106/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0475 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.8588 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.6370 - val_prc: 0.4340
Epoch 107/150
29/29 [==============================] - 6s 201ms/step - loss: 0.0497 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6444 - val_tp: 8.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 1.0000 - val_accuracy: 0.6667 - val_precision: 0.5333 - val_recall: 0.8889 - val_auc: 0.6481 - val_prc: 0.4369
Epoch 108/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0306 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5228 - val_tp: 5.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 4.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.5556 - val_auc: 0.6815 - val_prc: 0.4597
Epoch 109/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0238 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5728 - val_tp: 6.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 3.0000 - val_accuracy: 0.5833 - val_precision: 0.4615 - val_recall: 0.6667 - val_auc: 0.6889 - val_prc: 0.4670
Epoch 110/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0216 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.3391 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7148 - val_prc: 0.5073
Epoch 111/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0164 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6520 - val_tp: 8.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 1.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.8889 - val_auc: 0.6593 - val_prc: 0.4373
Epoch 112/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0236 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3961 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.7000 - val_prc: 0.5038
Epoch 113/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0113 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.9034 - val_tp: 7.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 2.0000 - val_accuracy: 0.5417 - val_precision: 0.4375 - val_recall: 0.7778 - val_auc: 0.6667 - val_prc: 0.4808
Epoch 114/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0524 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5860 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.6370 - val_prc: 0.4572
Epoch 115/150
29/29 [==============================] - 6s 201ms/step - loss: 0.0723 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9975 - prc: 0.9959 - val_loss: 4.4519 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6111 - val_prc: 0.5895
Epoch 116/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0839 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6600 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.6370 - val_prc: 0.5225
Epoch 117/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1030 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9861 - prc: 0.9846 - val_loss: 2.1225 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.6519 - val_prc: 0.4370
Epoch 118/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0572 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9987 - prc: 0.9980 - val_loss: 2.9734 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.5000 - val_prc: 0.3483
Epoch 119/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0498 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.0978 - val_tp: 2.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 7.0000 - val_accuracy: 0.5833 - val_precision: 0.4000 - val_recall: 0.2222 - val_auc: 0.6407 - val_prc: 0.5501
Epoch 120/150
29/29 [==============================] - 6s 200ms/step - loss: 0.0777 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9962 - prc: 0.9944 - val_loss: 3.4611 - val_tp: 6.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 3.0000 - val_accuracy: 0.4167 - val_precision: 0.3529 - val_recall: 0.6667 - val_auc: 0.4259 - val_prc: 0.3369
Epoch 121/150
29/29 [==============================] - 5s 175ms/step - loss: 0.0966 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9949 - prc: 0.9913 - val_loss: 1.6355 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.6481 - val_prc: 0.4467
Epoch 122/150
29/29 [==============================] - 5s 175ms/step - loss: 0.0975 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9924 - prc: 0.9901 - val_loss: 5.3627 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6667 - val_prc: 0.4737
Epoch 123/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0575 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4247 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.6296 - val_prc: 0.4429
Epoch 124/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0508 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4254 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.5074 - val_prc: 0.4519
Epoch 125/150
29/29 [==============================] - 6s 201ms/step - loss: 0.0282 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4721 - val_tp: 3.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 6.0000 - val_accuracy: 0.5000 - val_precision: 0.3333 - val_recall: 0.3333 - val_auc: 0.6148 - val_prc: 0.5433
Epoch 126/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0435 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5210 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.6630 - val_prc: 0.5017
Epoch 127/150
29/29 [==============================] - 5s 182ms/step - loss: 0.0587 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3495 - val_tp: 3.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 6.0000 - val_accuracy: 0.5417 - val_precision: 0.3750 - val_recall: 0.3333 - val_auc: 0.6741 - val_prc: 0.5087
Epoch 128/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0341 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.7384 - val_tp: 7.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 2.0000 - val_accuracy: 0.5833 - val_precision: 0.4667 - val_recall: 0.7778 - val_auc: 0.6000 - val_prc: 0.4126
Epoch 129/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0354 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5934 - val_tp: 8.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 1.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.8889 - val_auc: 0.6370 - val_prc: 0.4527
Epoch 130/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0356 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6407 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.5963 - val_prc: 0.4800
Epoch 131/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0248 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.9388 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.6037 - val_prc: 0.5653
Epoch 132/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0358 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6263 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.6370 - val_prc: 0.4450
Epoch 133/150
29/29 [==============================] - 5s 176ms/step - loss: 0.0149 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.7919 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.6037 - val_prc: 0.5565
Epoch 134/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0399 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.3672 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.6111 - val_prc: 0.5895
Epoch 135/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0111 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.8030 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.6111 - val_prc: 0.5895
Epoch 136/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0055 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.9866 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.6407 - val_prc: 0.6022
Epoch 137/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0820 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9975 - prc: 0.9959 - val_loss: 1.8939 - val_tp: 8.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 1.0000 - val_accuracy: 0.7083 - val_precision: 0.5714 - val_recall: 0.8889 - val_auc: 0.7185 - val_prc: 0.4880
Epoch 138/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0297 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5812 - val_tp: 5.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 4.0000 - val_accuracy: 0.5417 - val_precision: 0.4167 - val_recall: 0.5556 - val_auc: 0.6296 - val_prc: 0.4863
Epoch 139/150
29/29 [==============================] - 6s 201ms/step - loss: 0.0379 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4258 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.5815 - val_prc: 0.4501
Epoch 140/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0119 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3512 - val_tp: 4.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 5.0000 - val_accuracy: 0.6667 - val_precision: 0.5714 - val_recall: 0.4444 - val_auc: 0.7000 - val_prc: 0.6010
Epoch 141/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0464 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3362 - val_tp: 4.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 5.0000 - val_accuracy: 0.5417 - val_precision: 0.4000 - val_recall: 0.4444 - val_auc: 0.6593 - val_prc: 0.5819
Epoch 142/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0424 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4989 - val_tp: 8.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 1.0000 - val_accuracy: 0.6667 - val_precision: 0.5333 - val_recall: 0.8889 - val_auc: 0.6556 - val_prc: 0.5460
Epoch 143/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0245 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.9789 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.6185 - val_prc: 0.4106
Epoch 144/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0889 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9949 - prc: 0.9929 - val_loss: 2.0951 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.6333 - val_prc: 0.4392
Epoch 145/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0748 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.1505 - val_tp: 6.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 3.0000 - val_accuracy: 0.3750 - val_precision: 0.3333 - val_recall: 0.6667 - val_auc: 0.4259 - val_prc: 0.3118
Epoch 146/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0888 - tp: 22.0000 - fp: 2.0000 - tn: 34.0000 - fn: 0.0000e+00 - accuracy: 0.9655 - precision: 0.9167 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3046 - val_tp: 4.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 5.0000 - val_accuracy: 0.6667 - val_precision: 0.5714 - val_recall: 0.4444 - val_auc: 0.6481 - val_prc: 0.6198
Epoch 147/150
29/29 [==============================] - 6s 202ms/step - loss: 0.1112 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9924 - prc: 0.9870 - val_loss: 3.0559 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5778 - val_prc: 0.5134
Epoch 148/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1741 - tp: 18.0000 - fp: 2.0000 - tn: 34.0000 - fn: 4.0000 - accuracy: 0.8966 - precision: 0.9000 - recall: 0.8182 - auc: 0.9804 - prc: 0.9692 - val_loss: 2.1499 - val_tp: 3.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 6.0000 - val_accuracy: 0.6667 - val_precision: 0.6000 - val_recall: 0.3333 - val_auc: 0.5815 - val_prc: 0.5663
Epoch 149/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1287 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9785 - prc: 0.9799 - val_loss: 2.6137 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.5926 - val_prc: 0.5749
Epoch 150/150
29/29 [==============================] - 6s 203ms/step - loss: 0.0795 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4128 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.6593 - val_prc: 0.5844
Basic augmentation
The basic augmentation is very light since it just enables the brightness and contrast layers. The expected results are not much better with respect to the previous case.
model = build_model(augmentation=True,
rotation=False,
flip=False,
shift=False,
zoom=False,
shear=False,
brightness=True,
contrast=True)
performance["basic"] = train_model(model, training_dataset, validation_dataset)
Epoch 1/150
29/29 [==============================] - 10s 199ms/step - loss: 0.6830 - tp: 12.0000 - fp: 12.0000 - tn: 39.0000 - fn: 19.0000 - accuracy: 0.6220 - precision: 0.5000 - recall: 0.3871 - auc: 0.5569 - prc: 0.4748 - val_loss: 0.6913 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.6296 - val_prc: 0.4677
Epoch 2/150
29/29 [==============================] - 5s 177ms/step - loss: 0.6188 - tp: 10.0000 - fp: 4.0000 - tn: 32.0000 - fn: 12.0000 - accuracy: 0.7241 - precision: 0.7143 - recall: 0.4545 - auc: 0.7664 - prc: 0.7183 - val_loss: 0.7491 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6000 - val_prc: 0.5361
Epoch 3/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6501 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.6237 - prc: 0.5183 - val_loss: 0.7112 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6222 - val_prc: 0.5844
Epoch 4/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5945 - tp: 12.0000 - fp: 5.0000 - tn: 31.0000 - fn: 10.0000 - accuracy: 0.7414 - precision: 0.7059 - recall: 0.5455 - auc: 0.7311 - prc: 0.6222 - val_loss: 0.8578 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5963 - val_prc: 0.5271
Epoch 5/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6198 - tp: 4.0000 - fp: 2.0000 - tn: 34.0000 - fn: 18.0000 - accuracy: 0.6552 - precision: 0.6667 - recall: 0.1818 - auc: 0.6913 - prc: 0.6345 - val_loss: 0.6775 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6000 - val_prc: 0.5625
Epoch 6/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5820 - tp: 10.0000 - fp: 4.0000 - tn: 32.0000 - fn: 12.0000 - accuracy: 0.7241 - precision: 0.7143 - recall: 0.4545 - auc: 0.7620 - prc: 0.7166 - val_loss: 0.9705 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5963 - val_prc: 0.5628
Epoch 7/150
29/29 [==============================] - 5s 176ms/step - loss: 0.5588 - tp: 10.0000 - fp: 4.0000 - tn: 32.0000 - fn: 12.0000 - accuracy: 0.7241 - precision: 0.7143 - recall: 0.4545 - auc: 0.7519 - prc: 0.7334 - val_loss: 1.0259 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5778 - val_prc: 0.5460
Epoch 8/150
29/29 [==============================] - 5s 178ms/step - loss: 0.5384 - tp: 15.0000 - fp: 6.0000 - tn: 30.0000 - fn: 7.0000 - accuracy: 0.7759 - precision: 0.7143 - recall: 0.6818 - auc: 0.8030 - prc: 0.7375 - val_loss: 3.4091 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5333 - val_prc: 0.3913
Epoch 9/150
29/29 [==============================] - 5s 177ms/step - loss: 0.5811 - tp: 12.0000 - fp: 12.0000 - tn: 24.0000 - fn: 10.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.5455 - auc: 0.7273 - prc: 0.6568 - val_loss: 0.8861 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5778 - val_prc: 0.5455
Epoch 10/150
29/29 [==============================] - 6s 200ms/step - loss: 0.5691 - tp: 9.0000 - fp: 6.0000 - tn: 30.0000 - fn: 13.0000 - accuracy: 0.6724 - precision: 0.6000 - recall: 0.4091 - auc: 0.7727 - prc: 0.6987 - val_loss: 1.1090 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4630 - val_prc: 0.4555
Epoch 11/150
29/29 [==============================] - 5s 175ms/step - loss: 0.6058 - tp: 11.0000 - fp: 8.0000 - tn: 28.0000 - fn: 11.0000 - accuracy: 0.6724 - precision: 0.5789 - recall: 0.5000 - auc: 0.7279 - prc: 0.6410 - val_loss: 2.1531 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6296 - val_prc: 0.5617
Epoch 12/150
29/29 [==============================] - 5s 177ms/step - loss: 0.5140 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.8220 - prc: 0.7629 - val_loss: 2.8898 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4556 - val_prc: 0.3475
Epoch 13/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4759 - tp: 14.0000 - fp: 2.0000 - tn: 34.0000 - fn: 8.0000 - accuracy: 0.8276 - precision: 0.8750 - recall: 0.6364 - auc: 0.8693 - prc: 0.8204 - val_loss: 1.1536 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5667 - val_prc: 0.5347
Epoch 14/150
29/29 [==============================] - 5s 176ms/step - loss: 0.4612 - tp: 16.0000 - fp: 5.0000 - tn: 31.0000 - fn: 6.0000 - accuracy: 0.8103 - precision: 0.7619 - recall: 0.7273 - auc: 0.8668 - prc: 0.8601 - val_loss: 4.0509 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.3750
Epoch 15/150
29/29 [==============================] - 5s 177ms/step - loss: 0.5514 - tp: 13.0000 - fp: 11.0000 - tn: 25.0000 - fn: 9.0000 - accuracy: 0.6552 - precision: 0.5417 - recall: 0.5909 - auc: 0.7734 - prc: 0.6824 - val_loss: 2.7095 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4815 - val_prc: 0.4583
Epoch 16/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5104 - tp: 15.0000 - fp: 6.0000 - tn: 30.0000 - fn: 7.0000 - accuracy: 0.7759 - precision: 0.7143 - recall: 0.6818 - auc: 0.8378 - prc: 0.7721 - val_loss: 3.3760 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6111 - val_prc: 0.4402
Epoch 17/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4790 - tp: 16.0000 - fp: 5.0000 - tn: 31.0000 - fn: 6.0000 - accuracy: 0.8103 - precision: 0.7619 - recall: 0.7273 - auc: 0.8422 - prc: 0.7598 - val_loss: 0.7231 - val_tp: 5.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 4.0000 - val_accuracy: 0.4583 - val_precision: 0.3571 - val_recall: 0.5556 - val_auc: 0.4778 - val_prc: 0.5576
Epoch 18/150
29/29 [==============================] - 5s 176ms/step - loss: 0.4418 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.8908 - prc: 0.8472 - val_loss: 0.8642 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.5148 - val_prc: 0.5184
Epoch 19/150
29/29 [==============================] - 5s 176ms/step - loss: 0.4891 - tp: 10.0000 - fp: 1.0000 - tn: 35.0000 - fn: 12.0000 - accuracy: 0.7759 - precision: 0.9091 - recall: 0.4545 - auc: 0.8422 - prc: 0.8125 - val_loss: 1.3278 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5259 - val_prc: 0.5516
Epoch 20/150
29/29 [==============================] - 5s 177ms/step - loss: 0.4552 - tp: 13.0000 - fp: 3.0000 - tn: 33.0000 - fn: 9.0000 - accuracy: 0.7931 - precision: 0.8125 - recall: 0.5909 - auc: 0.8586 - prc: 0.8386 - val_loss: 2.7479 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4778 - val_prc: 0.4492
Epoch 21/150
29/29 [==============================] - 5s 179ms/step - loss: 0.3782 - tp: 16.0000 - fp: 3.0000 - tn: 33.0000 - fn: 6.0000 - accuracy: 0.8448 - precision: 0.8421 - recall: 0.7273 - auc: 0.9318 - prc: 0.9067 - val_loss: 1.4158 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6074 - val_prc: 0.5685
Epoch 22/150
29/29 [==============================] - 5s 177ms/step - loss: 0.4321 - tp: 15.0000 - fp: 4.0000 - tn: 32.0000 - fn: 7.0000 - accuracy: 0.8103 - precision: 0.7895 - recall: 0.6818 - auc: 0.8643 - prc: 0.8522 - val_loss: 3.3259 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6111 - val_prc: 0.4476
Epoch 23/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3929 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.9015 - prc: 0.8851 - val_loss: 1.3029 - val_tp: 8.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 1.0000 - val_accuracy: 0.3333 - val_precision: 0.3478 - val_recall: 0.8889 - val_auc: 0.4593 - val_prc: 0.5056
Epoch 24/150
29/29 [==============================] - 5s 176ms/step - loss: 0.4009 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.9040 - prc: 0.8784 - val_loss: 2.6127 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5630 - val_prc: 0.4837
Epoch 25/150
29/29 [==============================] - 6s 201ms/step - loss: 0.3749 - tp: 17.0000 - fp: 4.0000 - tn: 32.0000 - fn: 5.0000 - accuracy: 0.8448 - precision: 0.8095 - recall: 0.7727 - auc: 0.9129 - prc: 0.9011 - val_loss: 1.5429 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4852 - val_prc: 0.5009
Epoch 26/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3584 - tp: 15.0000 - fp: 2.0000 - tn: 34.0000 - fn: 7.0000 - accuracy: 0.8448 - precision: 0.8824 - recall: 0.6818 - auc: 0.9236 - prc: 0.8998 - val_loss: 1.2788 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.5074 - val_prc: 0.5531
Epoch 27/150
29/29 [==============================] - 6s 199ms/step - loss: 0.3122 - tp: 19.0000 - fp: 2.0000 - tn: 34.0000 - fn: 3.0000 - accuracy: 0.9138 - precision: 0.9048 - recall: 0.8636 - auc: 0.9665 - prc: 0.9604 - val_loss: 1.8011 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4963 - val_prc: 0.5184
Epoch 28/150
29/29 [==============================] - 5s 175ms/step - loss: 0.4442 - tp: 15.0000 - fp: 3.0000 - tn: 33.0000 - fn: 7.0000 - accuracy: 0.8276 - precision: 0.8333 - recall: 0.6818 - auc: 0.8567 - prc: 0.8369 - val_loss: 1.3424 - val_tp: 8.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 1.0000 - val_accuracy: 0.3333 - val_precision: 0.3478 - val_recall: 0.8889 - val_auc: 0.4852 - val_prc: 0.4913
Epoch 29/150
29/29 [==============================] - 5s 178ms/step - loss: 0.3409 - tp: 17.0000 - fp: 2.0000 - tn: 34.0000 - fn: 5.0000 - accuracy: 0.8793 - precision: 0.8947 - recall: 0.7727 - auc: 0.9362 - prc: 0.9189 - val_loss: 2.1606 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5037 - val_prc: 0.5351
Epoch 30/150
29/29 [==============================] - 5s 176ms/step - loss: 0.3147 - tp: 17.0000 - fp: 3.0000 - tn: 33.0000 - fn: 5.0000 - accuracy: 0.8621 - precision: 0.8500 - recall: 0.7727 - auc: 0.9438 - prc: 0.9278 - val_loss: 1.0792 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.5889 - val_prc: 0.5584
Epoch 31/150
29/29 [==============================] - 5s 179ms/step - loss: 0.3214 - tp: 17.0000 - fp: 4.0000 - tn: 32.0000 - fn: 5.0000 - accuracy: 0.8448 - precision: 0.8095 - recall: 0.7727 - auc: 0.9343 - prc: 0.9314 - val_loss: 3.0873 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6741 - val_prc: 0.4884
Epoch 32/150
29/29 [==============================] - 5s 177ms/step - loss: 0.3385 - tp: 19.0000 - fp: 4.0000 - tn: 32.0000 - fn: 3.0000 - accuracy: 0.8793 - precision: 0.8261 - recall: 0.8636 - auc: 0.9476 - prc: 0.9213 - val_loss: 1.8834 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6519 - val_prc: 0.4720
Epoch 33/150
29/29 [==============================] - 5s 177ms/step - loss: 0.2997 - tp: 18.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 4.0000 - accuracy: 0.9310 - precision: 1.0000 - recall: 0.8182 - auc: 0.9583 - prc: 0.9510 - val_loss: 1.0953 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.6111 - val_prc: 0.5667
Epoch 34/150
29/29 [==============================] - 5s 180ms/step - loss: 0.2365 - tp: 18.0000 - fp: 2.0000 - tn: 34.0000 - fn: 4.0000 - accuracy: 0.8966 - precision: 0.9000 - recall: 0.8182 - auc: 0.9779 - prc: 0.9683 - val_loss: 1.1344 - val_tp: 6.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 3.0000 - val_accuracy: 0.3333 - val_precision: 0.3158 - val_recall: 0.6667 - val_auc: 0.5148 - val_prc: 0.5397
Epoch 35/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1734 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9899 - prc: 0.9856 - val_loss: 2.4849 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5296 - val_prc: 0.3963
Epoch 36/150
29/29 [==============================] - 5s 180ms/step - loss: 0.2748 - tp: 17.0000 - fp: 1.0000 - tn: 35.0000 - fn: 5.0000 - accuracy: 0.8966 - precision: 0.9444 - recall: 0.7727 - auc: 0.9729 - prc: 0.9567 - val_loss: 2.0846 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5704 - val_prc: 0.4378
Epoch 37/150
29/29 [==============================] - 5s 177ms/step - loss: 0.2393 - tp: 18.0000 - fp: 2.0000 - tn: 34.0000 - fn: 4.0000 - accuracy: 0.8966 - precision: 0.9000 - recall: 0.8182 - auc: 0.9792 - prc: 0.9694 - val_loss: 1.2777 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7074 - val_prc: 0.5293
Epoch 38/150
29/29 [==============================] - 6s 201ms/step - loss: 0.1857 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9937 - prc: 0.9899 - val_loss: 1.1879 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.6037 - val_prc: 0.5722
Epoch 39/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1526 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9994 - prc: 0.9990 - val_loss: 1.7134 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6037 - val_prc: 0.5734
Epoch 40/150
29/29 [==============================] - 5s 178ms/step - loss: 0.2425 - tp: 18.0000 - fp: 3.0000 - tn: 33.0000 - fn: 4.0000 - accuracy: 0.8793 - precision: 0.8571 - recall: 0.8182 - auc: 0.9646 - prc: 0.9552 - val_loss: 1.0025 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.5741 - val_prc: 0.5739
Epoch 41/150
29/29 [==============================] - 5s 177ms/step - loss: 0.2049 - tp: 19.0000 - fp: 2.0000 - tn: 34.0000 - fn: 3.0000 - accuracy: 0.9138 - precision: 0.9048 - recall: 0.8636 - auc: 0.9867 - prc: 0.9788 - val_loss: 0.7786 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.6185 - val_prc: 0.5937
Epoch 42/150
29/29 [==============================] - 5s 178ms/step - loss: 0.2102 - tp: 18.0000 - fp: 1.0000 - tn: 35.0000 - fn: 4.0000 - accuracy: 0.9138 - precision: 0.9474 - recall: 0.8182 - auc: 0.9697 - prc: 0.9607 - val_loss: 3.9611 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5556 - val_prc: 0.4016
Epoch 43/150
29/29 [==============================] - 5s 178ms/step - loss: 0.2055 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9804 - prc: 0.9729 - val_loss: 0.8082 - val_tp: 7.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 2.0000 - val_accuracy: 0.7083 - val_precision: 0.5833 - val_recall: 0.7778 - val_auc: 0.6815 - val_prc: 0.6163
Epoch 44/150
29/29 [==============================] - 5s 178ms/step - loss: 0.2180 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9880 - prc: 0.9789 - val_loss: 2.1966 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.4178
Epoch 45/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2158 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9760 - prc: 0.9684 - val_loss: 2.3301 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6444 - val_prc: 0.5369
Epoch 46/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1186 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 2.6398 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6370 - val_prc: 0.4977
Epoch 47/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2241 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9893 - prc: 0.9840 - val_loss: 0.9055 - val_tp: 3.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 6.0000 - val_accuracy: 0.7083 - val_precision: 0.7500 - val_recall: 0.3333 - val_auc: 0.5889 - val_prc: 0.5996
Epoch 48/150
29/29 [==============================] - 6s 200ms/step - loss: 0.2135 - tp: 21.0000 - fp: 4.0000 - tn: 32.0000 - fn: 1.0000 - accuracy: 0.9138 - precision: 0.8400 - recall: 0.9545 - auc: 0.9798 - prc: 0.9763 - val_loss: 1.1924 - val_tp: 8.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 1.0000 - val_accuracy: 0.4583 - val_precision: 0.4000 - val_recall: 0.8889 - val_auc: 0.6815 - val_prc: 0.6382
Epoch 49/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1642 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9975 - prc: 0.9959 - val_loss: 1.0873 - val_tp: 6.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 3.0000 - val_accuracy: 0.5000 - val_precision: 0.4000 - val_recall: 0.6667 - val_auc: 0.5926 - val_prc: 0.5676
Epoch 50/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1233 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 2.4068 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6037 - val_prc: 0.4214
Epoch 51/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0946 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.2321 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.6593 - val_prc: 0.6299
Epoch 52/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1450 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9912 - prc: 0.9864 - val_loss: 3.7010 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6926 - val_prc: 0.4969
Epoch 53/150
29/29 [==============================] - 6s 202ms/step - loss: 0.2643 - tp: 16.0000 - fp: 3.0000 - tn: 33.0000 - fn: 6.0000 - accuracy: 0.8448 - precision: 0.8421 - recall: 0.7273 - auc: 0.9571 - prc: 0.9395 - val_loss: 1.5267 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6296 - val_prc: 0.4843
Epoch 54/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2133 - tp: 21.0000 - fp: 3.0000 - tn: 33.0000 - fn: 1.0000 - accuracy: 0.9310 - precision: 0.8750 - recall: 0.9545 - auc: 0.9823 - prc: 0.9808 - val_loss: 1.6550 - val_tp: 5.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 4.0000 - val_accuracy: 0.2500 - val_precision: 0.2632 - val_recall: 0.5556 - val_auc: 0.4259 - val_prc: 0.4297
Epoch 55/150
29/29 [==============================] - 5s 180ms/step - loss: 0.1688 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9975 - prc: 0.9961 - val_loss: 0.9434 - val_tp: 5.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 4.0000 - val_accuracy: 0.5417 - val_precision: 0.4167 - val_recall: 0.5556 - val_auc: 0.5926 - val_prc: 0.5287
Epoch 56/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1485 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9924 - prc: 0.9893 - val_loss: 1.1409 - val_tp: 7.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 2.0000 - val_accuracy: 0.5000 - val_precision: 0.4118 - val_recall: 0.7778 - val_auc: 0.6370 - val_prc: 0.5996
Epoch 57/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1526 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9962 - prc: 0.9936 - val_loss: 2.1477 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.5704 - val_prc: 0.4882
Epoch 58/150
29/29 [==============================] - 6s 200ms/step - loss: 0.1417 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9924 - prc: 0.9888 - val_loss: 1.6656 - val_tp: 7.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 2.0000 - val_accuracy: 0.3333 - val_precision: 0.3333 - val_recall: 0.7778 - val_auc: 0.5259 - val_prc: 0.5352
Epoch 59/150
29/29 [==============================] - 5s 177ms/step - loss: 0.2337 - tp: 16.0000 - fp: 1.0000 - tn: 35.0000 - fn: 6.0000 - accuracy: 0.8793 - precision: 0.9412 - recall: 0.7273 - auc: 0.9672 - prc: 0.9556 - val_loss: 2.4534 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6370 - val_prc: 0.4575
Epoch 60/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1521 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9912 - prc: 0.9864 - val_loss: 3.3470 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6296 - val_prc: 0.4461
Epoch 61/150
29/29 [==============================] - 5s 176ms/step - loss: 0.1245 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9924 - prc: 0.9893 - val_loss: 1.4928 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.6444 - val_prc: 0.5180
Epoch 62/150
29/29 [==============================] - 6s 203ms/step - loss: 0.1665 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9937 - prc: 0.9889 - val_loss: 2.6169 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5852 - val_prc: 0.4785
Epoch 63/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0910 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.0362 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5481 - val_prc: 0.4198
Epoch 64/150
29/29 [==============================] - 6s 203ms/step - loss: 0.1491 - tp: 18.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 4.0000 - accuracy: 0.9310 - precision: 1.0000 - recall: 0.8182 - auc: 0.9918 - prc: 0.9882 - val_loss: 3.3631 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6259 - val_prc: 0.4418
Epoch 65/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0948 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9962 - prc: 0.9940 - val_loss: 1.4223 - val_tp: 7.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 2.0000 - val_accuracy: 0.4583 - val_precision: 0.3889 - val_recall: 0.7778 - val_auc: 0.6259 - val_prc: 0.6189
Epoch 66/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0844 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.5829 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5556 - val_prc: 0.4016
Epoch 67/150
29/29 [==============================] - 5s 177ms/step - loss: 0.1120 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9937 - prc: 0.9904 - val_loss: 3.1984 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4889 - val_prc: 0.3933
Epoch 68/150
29/29 [==============================] - 6s 201ms/step - loss: 0.2126 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 0.9646 - prc: 0.9588 - val_loss: 5.4056 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6000 - val_prc: 0.4286
Epoch 69/150
29/29 [==============================] - 5s 178ms/step - loss: 0.2655 - tp: 16.0000 - fp: 2.0000 - tn: 34.0000 - fn: 6.0000 - accuracy: 0.8621 - precision: 0.8889 - recall: 0.7273 - auc: 0.9628 - prc: 0.9417 - val_loss: 1.1726 - val_tp: 6.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 3.0000 - val_accuracy: 0.3750 - val_precision: 0.3333 - val_recall: 0.6667 - val_auc: 0.5704 - val_prc: 0.5607
Epoch 70/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1365 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9937 - prc: 0.9904 - val_loss: 3.3981 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5370 - val_prc: 0.3859
Epoch 71/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1574 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9861 - prc: 0.9806 - val_loss: 3.3246 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5444 - val_prc: 0.4212
Epoch 72/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1275 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.1590 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5556 - val_prc: 0.4016
Epoch 73/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0838 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.9734 - val_tp: 8.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 1.0000 - val_accuracy: 0.3750 - val_precision: 0.3636 - val_recall: 0.8889 - val_auc: 0.5185 - val_prc: 0.4171
Epoch 74/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1088 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9962 - prc: 0.9936 - val_loss: 4.0157 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4667 - val_prc: 0.3500
Epoch 75/150
29/29 [==============================] - 5s 181ms/step - loss: 0.1446 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9899 - prc: 0.9837 - val_loss: 2.9612 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5778 - val_prc: 0.4154
Epoch 76/150
29/29 [==============================] - 6s 203ms/step - loss: 0.0713 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 0.9987 - prc: 0.9980 - val_loss: 4.5733 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6000 - val_prc: 0.4286
Epoch 77/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0964 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.7162 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5630 - val_prc: 0.3880
Epoch 78/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1358 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9874 - prc: 0.9827 - val_loss: 1.3227 - val_tp: 7.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 2.0000 - val_accuracy: 0.5417 - val_precision: 0.4375 - val_recall: 0.7778 - val_auc: 0.6333 - val_prc: 0.4920
Epoch 79/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0856 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 2.6552 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5185 - val_prc: 0.4217
Epoch 80/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1499 - tp: 18.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 4.0000 - accuracy: 0.9310 - precision: 1.0000 - recall: 0.8182 - auc: 0.9912 - prc: 0.9862 - val_loss: 1.2554 - val_tp: 4.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 5.0000 - val_accuracy: 0.5417 - val_precision: 0.4000 - val_recall: 0.4444 - val_auc: 0.5296 - val_prc: 0.5386
Epoch 81/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0599 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.0355 - val_tp: 7.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 2.0000 - val_accuracy: 0.3750 - val_precision: 0.3500 - val_recall: 0.7778 - val_auc: 0.5185 - val_prc: 0.4231
Epoch 82/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0777 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9962 - prc: 0.9944 - val_loss: 1.7000 - val_tp: 6.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 3.0000 - val_accuracy: 0.3750 - val_precision: 0.3333 - val_recall: 0.6667 - val_auc: 0.5333 - val_prc: 0.4734
Epoch 83/150
29/29 [==============================] - 6s 201ms/step - loss: 0.0676 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.8261 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5407 - val_prc: 0.4026
Epoch 84/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0933 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.7199 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5296 - val_prc: 0.3871
Epoch 85/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0603 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 5.5722 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5667 - val_prc: 0.4091
Epoch 86/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0923 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 2.8736 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6556 - val_prc: 0.4638
Epoch 87/150
29/29 [==============================] - 6s 204ms/step - loss: 0.0645 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.7041 - val_tp: 5.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 4.0000 - val_accuracy: 0.3750 - val_precision: 0.3125 - val_recall: 0.5556 - val_auc: 0.4741 - val_prc: 0.4138
Epoch 88/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0570 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.4840 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5778 - val_prc: 0.4226
Epoch 89/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0424 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.4750 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5407 - val_prc: 0.3916
Epoch 90/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1142 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9880 - prc: 0.9861 - val_loss: 3.5888 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4963 - val_prc: 0.3667
Epoch 91/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0507 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.0560 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.3679
Epoch 92/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0612 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.2421 - val_tp: 7.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 2.0000 - val_accuracy: 0.4167 - val_precision: 0.3684 - val_recall: 0.7778 - val_auc: 0.5333 - val_prc: 0.4312
Epoch 93/150
29/29 [==============================] - 5s 178ms/step - loss: 0.1112 - tp: 21.0000 - fp: 3.0000 - tn: 33.0000 - fn: 1.0000 - accuracy: 0.9310 - precision: 0.8750 - recall: 0.9545 - auc: 0.9937 - prc: 0.9914 - val_loss: 2.1516 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.7259 - val_prc: 0.6492
Epoch 94/150
29/29 [==============================] - 5s 181ms/step - loss: 0.1179 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9937 - prc: 0.9914 - val_loss: 1.4414 - val_tp: 6.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 3.0000 - val_accuracy: 0.5000 - val_precision: 0.4000 - val_recall: 0.6667 - val_auc: 0.6259 - val_prc: 0.5550
Epoch 95/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1062 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9937 - prc: 0.9914 - val_loss: 2.7095 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.4815 - val_prc: 0.3770
Epoch 96/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0810 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.9633 - val_tp: 5.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 4.0000 - val_accuracy: 0.4167 - val_precision: 0.3333 - val_recall: 0.5556 - val_auc: 0.4704 - val_prc: 0.4114
Epoch 97/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0859 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9994 - prc: 0.9990 - val_loss: 1.9116 - val_tp: 5.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 4.0000 - val_accuracy: 0.3333 - val_precision: 0.2941 - val_recall: 0.5556 - val_auc: 0.4630 - val_prc: 0.3964
Epoch 98/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0968 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9886 - prc: 0.9866 - val_loss: 2.7720 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5778 - val_prc: 0.4204
Epoch 99/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0579 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.6175 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5222 - val_prc: 0.3843
Epoch 100/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0369 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.2924 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4667 - val_prc: 0.3500
Epoch 101/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0925 - tp: 22.0000 - fp: 2.0000 - tn: 34.0000 - fn: 0.0000e+00 - accuracy: 0.9655 - precision: 0.9167 - recall: 1.0000 - auc: 0.9962 - prc: 0.9936 - val_loss: 2.2516 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5259 - val_prc: 0.4097
Epoch 102/150
29/29 [==============================] - 6s 203ms/step - loss: 0.0926 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9962 - prc: 0.9936 - val_loss: 2.0684 - val_tp: 8.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 1.0000 - val_accuracy: 0.3750 - val_precision: 0.3636 - val_recall: 0.8889 - val_auc: 0.5407 - val_prc: 0.4287
Epoch 103/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0658 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.8156 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.4815 - val_prc: 0.3588
Epoch 104/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0603 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.3681 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.4667 - val_prc: 0.3429
Epoch 105/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0254 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.4728 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4519 - val_prc: 0.3385
Epoch 106/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0220 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.9446 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5185 - val_prc: 0.4030
Epoch 107/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0149 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.6206 - val_tp: 8.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 1.0000 - val_accuracy: 0.3750 - val_precision: 0.3636 - val_recall: 0.8889 - val_auc: 0.5037 - val_prc: 0.4005
Epoch 108/150
29/29 [==============================] - 6s 202ms/step - loss: 0.0628 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.1908 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.6370 - val_prc: 0.5367
Epoch 109/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0694 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.3011 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.4222 - val_prc: 0.3490
Epoch 110/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0740 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.0451 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.6074 - val_prc: 0.4386
Epoch 111/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0756 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9962 - prc: 0.9936 - val_loss: 3.3727 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.5852 - val_prc: 0.4179
Epoch 112/150
29/29 [==============================] - 5s 179ms/step - loss: 0.1125 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9924 - prc: 0.9893 - val_loss: 1.3505 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6111 - val_prc: 0.5408
Epoch 113/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0879 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9949 - prc: 0.9929 - val_loss: 6.0629 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5667 - val_prc: 0.4091
Epoch 114/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0532 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.3074 - val_tp: 5.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 4.0000 - val_accuracy: 0.3333 - val_precision: 0.2941 - val_recall: 0.5556 - val_auc: 0.4852 - val_prc: 0.4030
Epoch 115/150
29/29 [==============================] - 6s 201ms/step - loss: 0.1137 - tp: 20.0000 - fp: 2.0000 - tn: 34.0000 - fn: 2.0000 - accuracy: 0.9310 - precision: 0.9091 - recall: 0.9091 - auc: 0.9924 - prc: 0.9886 - val_loss: 1.7581 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.4556 - val_prc: 0.4986
Epoch 116/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0722 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.2569 - val_tp: 6.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 3.0000 - val_accuracy: 0.3750 - val_precision: 0.3333 - val_recall: 0.6667 - val_auc: 0.4556 - val_prc: 0.3915
Epoch 117/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0887 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.6542 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.5111 - val_prc: 0.4582
Epoch 118/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0650 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3462 - val_tp: 5.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 4.0000 - val_accuracy: 0.5000 - val_precision: 0.3846 - val_recall: 0.5556 - val_auc: 0.5481 - val_prc: 0.5434
Epoch 119/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0646 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.4556 - val_tp: 5.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 4.0000 - val_accuracy: 0.5417 - val_precision: 0.4167 - val_recall: 0.5556 - val_auc: 0.5185 - val_prc: 0.4586
Epoch 120/150
29/29 [==============================] - 6s 204ms/step - loss: 0.0925 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9949 - prc: 0.9929 - val_loss: 1.4570 - val_tp: 4.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 5.0000 - val_accuracy: 0.5000 - val_precision: 0.3636 - val_recall: 0.4444 - val_auc: 0.5111 - val_prc: 0.5224
Epoch 121/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0649 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5245 - val_tp: 5.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 4.0000 - val_accuracy: 0.3750 - val_precision: 0.3125 - val_recall: 0.5556 - val_auc: 0.5185 - val_prc: 0.4232
Epoch 122/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0733 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 1.7170 - val_tp: 5.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 4.0000 - val_accuracy: 0.4167 - val_precision: 0.3333 - val_recall: 0.5556 - val_auc: 0.4926 - val_prc: 0.4044
Epoch 123/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0667 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.8725 - val_tp: 7.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 2.0000 - val_accuracy: 0.4167 - val_precision: 0.3684 - val_recall: 0.7778 - val_auc: 0.5259 - val_prc: 0.3983
Epoch 124/150
29/29 [==============================] - 5s 177ms/step - loss: 0.0969 - tp: 19.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 3.0000 - accuracy: 0.9483 - precision: 1.0000 - recall: 0.8636 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.0981 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7259 - val_prc: 0.5298
Epoch 125/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0381 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.9360 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.7000 - val_prc: 0.5000
Epoch 126/150
29/29 [==============================] - 6s 203ms/step - loss: 0.0656 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9994 - prc: 0.9990 - val_loss: 4.9518 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6000 - val_prc: 0.4286
Epoch 127/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0255 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.6203 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6481 - val_prc: 0.4632
Epoch 128/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0593 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.5356 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5481 - val_prc: 0.4167
Epoch 129/150
29/29 [==============================] - 5s 185ms/step - loss: 0.0628 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 0.9975 - prc: 0.9961 - val_loss: 2.4770 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7333 - val_prc: 0.5378
Epoch 130/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0474 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.2094 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6593 - val_prc: 0.4694
Epoch 131/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0504 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.4861 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5407 - val_prc: 0.3911
Epoch 132/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0231 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.0904 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.4852 - val_prc: 0.3634
Epoch 133/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0270 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 4.2913 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.4481 - val_prc: 0.3385
Epoch 134/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0095 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.4317 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5222 - val_prc: 0.3846
Epoch 135/150
29/29 [==============================] - 5s 182ms/step - loss: 0.0220 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.4199 - val_tp: 5.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 4.0000 - val_accuracy: 0.3333 - val_precision: 0.2941 - val_recall: 0.5556 - val_auc: 0.4852 - val_prc: 0.3649
Epoch 136/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0174 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.6998 - val_tp: 6.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 3.0000 - val_accuracy: 0.3750 - val_precision: 0.3333 - val_recall: 0.6667 - val_auc: 0.4593 - val_prc: 0.3626
Epoch 137/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0079 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.4095 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.3775
Epoch 138/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0085 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 3.3366 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5037 - val_prc: 0.3786
Epoch 139/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0092 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.8076 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.4259 - val_prc: 0.3315
Epoch 140/150
29/29 [==============================] - 6s 203ms/step - loss: 0.0059 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.4575 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.4963 - val_prc: 0.4059
Epoch 141/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0131 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.2473 - val_tp: 8.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 1.0000 - val_accuracy: 0.4583 - val_precision: 0.4000 - val_recall: 0.8889 - val_auc: 0.5185 - val_prc: 0.4143
Epoch 142/150
29/29 [==============================] - 5s 182ms/step - loss: 0.0465 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.7348 - val_tp: 5.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 4.0000 - val_accuracy: 0.4583 - val_precision: 0.3571 - val_recall: 0.5556 - val_auc: 0.5333 - val_prc: 0.4518
Epoch 143/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0906 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.6769 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.5963 - val_prc: 0.5623
Epoch 144/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0388 - tp: 22.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 0.0000e+00 - accuracy: 1.0000 - precision: 1.0000 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.3065 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.5741 - val_prc: 0.5469
Epoch 145/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0332 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 1.5890 - val_tp: 7.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 2.0000 - val_accuracy: 0.5417 - val_precision: 0.4375 - val_recall: 0.7778 - val_auc: 0.6148 - val_prc: 0.4760
Epoch 146/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0701 - tp: 20.0000 - fp: 1.0000 - tn: 35.0000 - fn: 2.0000 - accuracy: 0.9483 - precision: 0.9524 - recall: 0.9091 - auc: 0.9962 - prc: 0.9940 - val_loss: 3.6880 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.4481 - val_prc: 0.3441
Epoch 147/150
29/29 [==============================] - 5s 180ms/step - loss: 0.0342 - tp: 22.0000 - fp: 1.0000 - tn: 35.0000 - fn: 0.0000e+00 - accuracy: 0.9828 - precision: 0.9565 - recall: 1.0000 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.1409 - val_tp: 5.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 4.0000 - val_accuracy: 0.3750 - val_precision: 0.3125 - val_recall: 0.5556 - val_auc: 0.4926 - val_prc: 0.3831
Epoch 148/150
29/29 [==============================] - 5s 178ms/step - loss: 0.0566 - tp: 21.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 1.0000 - accuracy: 0.9828 - precision: 1.0000 - recall: 0.9545 - auc: 1.0000 - prc: 1.0000 - val_loss: 2.9883 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6000 - val_prc: 0.4391
Epoch 149/150
29/29 [==============================] - 5s 179ms/step - loss: 0.0578 - tp: 21.0000 - fp: 1.0000 - tn: 35.0000 - fn: 1.0000 - accuracy: 0.9655 - precision: 0.9545 - recall: 0.9545 - auc: 0.9987 - prc: 0.9980 - val_loss: 4.5376 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5852 - val_prc: 0.4203
Epoch 150/150
29/29 [==============================] - 5s 181ms/step - loss: 0.0794 - tp: 20.0000 - fp: 0.0000e+00 - tn: 36.0000 - fn: 2.0000 - accuracy: 0.9655 - precision: 1.0000 - recall: 0.9091 - auc: 0.9975 - prc: 0.9959 - val_loss: 3.9708 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6667 - val_prc: 0.4737
Intermediate augmentation
Additional layers, i.e., rotation, flip and shift, are enabled which will deeply enrich the training dataset.
model = build_model(augmentation=True,
rotation=True,
flip=True,
shift=True,
zoom=False,
shear=False,
brightness=True,
contrast=True)
performance["intermediate"] = train_model(model, training_dataset, validation_dataset)
Epoch 1/150
29/29 [==============================] - 10s 199ms/step - loss: 0.7231 - tp: 16.0000 - fp: 27.0000 - tn: 24.0000 - fn: 15.0000 - accuracy: 0.4878 - precision: 0.3721 - recall: 0.5161 - auc: 0.4956 - prc: 0.3989 - val_loss: 0.6800 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5000 - val_prc: 0.3750
Epoch 2/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6889 - tp: 3.0000 - fp: 8.0000 - tn: 28.0000 - fn: 19.0000 - accuracy: 0.5345 - precision: 0.2727 - recall: 0.1364 - auc: 0.4356 - prc: 0.3383 - val_loss: 0.6677 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.3333 - val_prc: 0.2886
Epoch 3/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6853 - tp: 4.0000 - fp: 4.0000 - tn: 32.0000 - fn: 18.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.1818 - auc: 0.4470 - prc: 0.3943 - val_loss: 0.6686 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4000 - val_prc: 0.3155
Epoch 4/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6844 - tp: 1.0000 - fp: 5.0000 - tn: 31.0000 - fn: 21.0000 - accuracy: 0.5517 - precision: 0.1667 - recall: 0.0455 - auc: 0.4691 - prc: 0.3680 - val_loss: 0.7572 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4778 - val_prc: 0.3643
Epoch 5/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6479 - tp: 4.0000 - fp: 6.0000 - tn: 30.0000 - fn: 18.0000 - accuracy: 0.5862 - precision: 0.4000 - recall: 0.1818 - auc: 0.6086 - prc: 0.4274 - val_loss: 0.9019 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4000 - val_prc: 0.3155
Epoch 6/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6591 - tp: 6.0000 - fp: 8.0000 - tn: 28.0000 - fn: 16.0000 - accuracy: 0.5862 - precision: 0.4286 - recall: 0.2727 - auc: 0.5922 - prc: 0.4135 - val_loss: 0.7039 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4630 - val_prc: 0.3416
Epoch 7/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6428 - tp: 9.0000 - fp: 10.0000 - tn: 26.0000 - fn: 13.0000 - accuracy: 0.6034 - precision: 0.4737 - recall: 0.4091 - auc: 0.6345 - prc: 0.4728 - val_loss: 0.6765 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4630 - val_prc: 0.3887
Epoch 8/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6761 - tp: 3.0000 - fp: 5.0000 - tn: 31.0000 - fn: 19.0000 - accuracy: 0.5862 - precision: 0.3750 - recall: 0.1364 - auc: 0.5038 - prc: 0.3718 - val_loss: 1.3303 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4111 - val_prc: 0.3283
Epoch 9/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6448 - tp: 3.0000 - fp: 3.0000 - tn: 33.0000 - fn: 19.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.1364 - auc: 0.6635 - prc: 0.5027 - val_loss: 1.3146 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5000 - val_prc: 0.3750
Epoch 10/150
29/29 [==============================] - 6s 202ms/step - loss: 0.7098 - tp: 2.0000 - fp: 8.0000 - tn: 28.0000 - fn: 20.0000 - accuracy: 0.5172 - precision: 0.2000 - recall: 0.0909 - auc: 0.4369 - prc: 0.3235 - val_loss: 1.2832 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6556 - val_prc: 0.5505
Epoch 11/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6728 - tp: 2.0000 - fp: 5.0000 - tn: 31.0000 - fn: 20.0000 - accuracy: 0.5690 - precision: 0.2857 - recall: 0.0909 - auc: 0.5145 - prc: 0.3877 - val_loss: 1.0651 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5444 - val_prc: 0.4924
Epoch 12/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6299 - tp: 4.0000 - fp: 3.0000 - tn: 33.0000 - fn: 18.0000 - accuracy: 0.6379 - precision: 0.5714 - recall: 0.1818 - auc: 0.6604 - prc: 0.5622 - val_loss: 0.7223 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5889 - val_prc: 0.3991
Epoch 13/150
29/29 [==============================] - 5s 177ms/step - loss: 0.7063 - tp: 2.0000 - fp: 6.0000 - tn: 30.0000 - fn: 20.0000 - accuracy: 0.5517 - precision: 0.2500 - recall: 0.0909 - auc: 0.4539 - prc: 0.3761 - val_loss: 0.8667 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4407 - val_prc: 0.3629
Epoch 14/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6713 - tp: 3.0000 - fp: 5.0000 - tn: 31.0000 - fn: 19.0000 - accuracy: 0.5862 - precision: 0.3750 - recall: 0.1364 - auc: 0.5139 - prc: 0.4051 - val_loss: 0.6503 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6333 - val_prc: 0.5285
Epoch 15/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6131 - tp: 7.0000 - fp: 4.0000 - tn: 32.0000 - fn: 15.0000 - accuracy: 0.6724 - precision: 0.6364 - recall: 0.3182 - auc: 0.7153 - prc: 0.5919 - val_loss: 0.9687 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5074 - val_prc: 0.4616
Epoch 16/150
29/29 [==============================] - 6s 203ms/step - loss: 0.6645 - tp: 1.0000 - fp: 5.0000 - tn: 31.0000 - fn: 21.0000 - accuracy: 0.5517 - precision: 0.1667 - recall: 0.0455 - auc: 0.5657 - prc: 0.3811 - val_loss: 1.1999 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.3296 - val_prc: 0.3140
Epoch 17/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6871 - tp: 2.0000 - fp: 4.0000 - tn: 32.0000 - fn: 20.0000 - accuracy: 0.5862 - precision: 0.3333 - recall: 0.0909 - auc: 0.5051 - prc: 0.3926 - val_loss: 1.1274 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.3074 - val_prc: 0.3098
Epoch 18/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6332 - tp: 4.0000 - fp: 3.0000 - tn: 33.0000 - fn: 18.0000 - accuracy: 0.6379 - precision: 0.5714 - recall: 0.1818 - auc: 0.6793 - prc: 0.4978 - val_loss: 0.7809 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5037 - val_prc: 0.3814
Epoch 19/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6442 - tp: 8.0000 - fp: 6.0000 - tn: 30.0000 - fn: 14.0000 - accuracy: 0.6552 - precision: 0.5714 - recall: 0.3636 - auc: 0.6016 - prc: 0.5000 - val_loss: 0.6405 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.6556 - val_prc: 0.6124
Epoch 20/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6440 - tp: 9.0000 - fp: 10.0000 - tn: 26.0000 - fn: 13.0000 - accuracy: 0.6034 - precision: 0.4737 - recall: 0.4091 - auc: 0.6654 - prc: 0.5345 - val_loss: 0.9431 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6741 - val_prc: 0.6805
Epoch 21/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6616 - tp: 11.0000 - fp: 7.0000 - tn: 29.0000 - fn: 11.0000 - accuracy: 0.6897 - precision: 0.6111 - recall: 0.5000 - auc: 0.6477 - prc: 0.5794 - val_loss: 0.6928 - val_tp: 5.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 4.0000 - val_accuracy: 0.5000 - val_precision: 0.3846 - val_recall: 0.5556 - val_auc: 0.5481 - val_prc: 0.5116
Epoch 22/150
29/29 [==============================] - 5s 180ms/step - loss: 0.7111 - tp: 2.0000 - fp: 6.0000 - tn: 30.0000 - fn: 20.0000 - accuracy: 0.5517 - precision: 0.2500 - recall: 0.0909 - auc: 0.4217 - prc: 0.3235 - val_loss: 0.6896 - val_tp: 0.0000e+00 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 9.0000 - val_accuracy: 0.5417 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4407 - val_prc: 0.3527
Epoch 23/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6780 - tp: 5.0000 - fp: 3.0000 - tn: 33.0000 - fn: 17.0000 - accuracy: 0.6552 - precision: 0.6250 - recall: 0.2273 - auc: 0.6162 - prc: 0.4667 - val_loss: 0.7727 - val_tp: 6.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 3.0000 - val_accuracy: 0.3750 - val_precision: 0.3333 - val_recall: 0.6667 - val_auc: 0.3593 - val_prc: 0.3773
Epoch 24/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6768 - tp: 2.0000 - fp: 3.0000 - tn: 33.0000 - fn: 20.0000 - accuracy: 0.6034 - precision: 0.4000 - recall: 0.0909 - auc: 0.5347 - prc: 0.3901 - val_loss: 0.7188 - val_tp: 1.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 8.0000 - val_accuracy: 0.5833 - val_precision: 0.3333 - val_recall: 0.1111 - val_auc: 0.3074 - val_prc: 0.3651
Epoch 25/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6734 - tp: 2.0000 - fp: 4.0000 - tn: 32.0000 - fn: 20.0000 - accuracy: 0.5862 - precision: 0.3333 - recall: 0.0909 - auc: 0.4905 - prc: 0.4147 - val_loss: 0.7435 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.3370 - val_prc: 0.3695
Epoch 26/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6894 - tp: 5.0000 - fp: 5.0000 - tn: 31.0000 - fn: 17.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2273 - auc: 0.5271 - prc: 0.4133 - val_loss: 0.7057 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.3741 - val_prc: 0.3137
Epoch 27/150
29/29 [==============================] - 6s 202ms/step - loss: 0.6588 - tp: 3.0000 - fp: 2.0000 - tn: 34.0000 - fn: 19.0000 - accuracy: 0.6379 - precision: 0.6000 - recall: 0.1364 - auc: 0.6206 - prc: 0.4957 - val_loss: 0.6932 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4296 - val_prc: 0.3303
Epoch 28/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6489 - tp: 2.0000 - fp: 2.0000 - tn: 34.0000 - fn: 20.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.0909 - auc: 0.5884 - prc: 0.4461 - val_loss: 0.7580 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.3778 - val_prc: 0.2952
Epoch 29/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6667 - tp: 4.0000 - fp: 4.0000 - tn: 32.0000 - fn: 18.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.1818 - auc: 0.5745 - prc: 0.4509 - val_loss: 0.6758 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.4407 - val_prc: 0.4427
Epoch 30/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6734 - tp: 7.0000 - fp: 6.0000 - tn: 30.0000 - fn: 15.0000 - accuracy: 0.6379 - precision: 0.5385 - recall: 0.3182 - auc: 0.5568 - prc: 0.4381 - val_loss: 0.7776 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5963 - val_prc: 0.3982
Epoch 31/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6876 - tp: 6.0000 - fp: 8.0000 - tn: 28.0000 - fn: 16.0000 - accuracy: 0.5862 - precision: 0.4286 - recall: 0.2727 - auc: 0.5366 - prc: 0.3830 - val_loss: 0.7346 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.4111 - val_prc: 0.4668
Epoch 32/150
29/29 [==============================] - 6s 202ms/step - loss: 0.6331 - tp: 6.0000 - fp: 6.0000 - tn: 30.0000 - fn: 16.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2727 - auc: 0.6610 - prc: 0.4939 - val_loss: 0.6994 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6926 - val_prc: 0.6041
Epoch 33/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6269 - tp: 8.0000 - fp: 5.0000 - tn: 31.0000 - fn: 14.0000 - accuracy: 0.6724 - precision: 0.6154 - recall: 0.3636 - auc: 0.6629 - prc: 0.5904 - val_loss: 0.6840 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.6593 - val_prc: 0.5837
Epoch 34/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6252 - tp: 9.0000 - fp: 6.0000 - tn: 30.0000 - fn: 13.0000 - accuracy: 0.6724 - precision: 0.6000 - recall: 0.4091 - auc: 0.6629 - prc: 0.5198 - val_loss: 0.7985 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.5630 - val_prc: 0.5478
Epoch 35/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6482 - tp: 3.0000 - fp: 3.0000 - tn: 33.0000 - fn: 19.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.1364 - auc: 0.6042 - prc: 0.4433 - val_loss: 0.8125 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5889 - val_prc: 0.5534
Epoch 36/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6576 - tp: 8.0000 - fp: 6.0000 - tn: 30.0000 - fn: 14.0000 - accuracy: 0.6552 - precision: 0.5714 - recall: 0.3636 - auc: 0.5878 - prc: 0.4602 - val_loss: 0.8182 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6111 - val_prc: 0.6427
Epoch 37/150
29/29 [==============================] - 6s 202ms/step - loss: 0.5779 - tp: 9.0000 - fp: 3.0000 - tn: 33.0000 - fn: 13.0000 - accuracy: 0.7241 - precision: 0.7500 - recall: 0.4091 - auc: 0.7557 - prc: 0.6339 - val_loss: 0.8414 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6000 - val_prc: 0.5591
Epoch 38/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6377 - tp: 6.0000 - fp: 6.0000 - tn: 30.0000 - fn: 16.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2727 - auc: 0.6345 - prc: 0.5422 - val_loss: 0.8881 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5037 - val_prc: 0.3854
Epoch 39/150
29/29 [==============================] - 5s 178ms/step - loss: 0.5844 - tp: 9.0000 - fp: 4.0000 - tn: 32.0000 - fn: 13.0000 - accuracy: 0.7069 - precision: 0.6923 - recall: 0.4091 - auc: 0.7298 - prc: 0.6593 - val_loss: 0.8948 - val_tp: 8.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 1.0000 - val_accuracy: 0.3333 - val_precision: 0.3478 - val_recall: 0.8889 - val_auc: 0.4148 - val_prc: 0.3516
Epoch 40/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6297 - tp: 12.0000 - fp: 7.0000 - tn: 29.0000 - fn: 10.0000 - accuracy: 0.7069 - precision: 0.6316 - recall: 0.5455 - auc: 0.6635 - prc: 0.5439 - val_loss: 0.6382 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6778 - val_prc: 0.5666
Epoch 41/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6754 - tp: 8.0000 - fp: 10.0000 - tn: 26.0000 - fn: 14.0000 - accuracy: 0.5862 - precision: 0.4444 - recall: 0.3636 - auc: 0.6023 - prc: 0.4386 - val_loss: 0.5928 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.7000 - val_prc: 0.5393
Epoch 42/150
29/29 [==============================] - 6s 204ms/step - loss: 0.6478 - tp: 6.0000 - fp: 5.0000 - tn: 31.0000 - fn: 16.0000 - accuracy: 0.6379 - precision: 0.5455 - recall: 0.2727 - auc: 0.6143 - prc: 0.4462 - val_loss: 0.7146 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7000 - val_prc: 0.5030
Epoch 43/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6467 - tp: 5.0000 - fp: 6.0000 - tn: 30.0000 - fn: 17.0000 - accuracy: 0.6034 - precision: 0.4545 - recall: 0.2273 - auc: 0.6136 - prc: 0.5181 - val_loss: 0.6625 - val_tp: 8.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 1.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.8889 - val_auc: 0.7444 - val_prc: 0.6732
Epoch 44/150
29/29 [==============================] - 6s 205ms/step - loss: 0.5776 - tp: 10.0000 - fp: 3.0000 - tn: 33.0000 - fn: 12.0000 - accuracy: 0.7414 - precision: 0.7692 - recall: 0.4545 - auc: 0.7740 - prc: 0.6486 - val_loss: 0.8812 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.7704 - val_prc: 0.6667
Epoch 45/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6245 - tp: 6.0000 - fp: 6.0000 - tn: 30.0000 - fn: 16.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2727 - auc: 0.6818 - prc: 0.4868 - val_loss: 0.6010 - val_tp: 6.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 3.0000 - val_accuracy: 0.6667 - val_precision: 0.5455 - val_recall: 0.6667 - val_auc: 0.7259 - val_prc: 0.6229
Epoch 46/150
29/29 [==============================] - 6s 201ms/step - loss: 0.5504 - tp: 12.0000 - fp: 7.0000 - tn: 29.0000 - fn: 10.0000 - accuracy: 0.7069 - precision: 0.6316 - recall: 0.5455 - auc: 0.8005 - prc: 0.6214 - val_loss: 0.6673 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7704 - val_prc: 0.6662
Epoch 47/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6320 - tp: 10.0000 - fp: 7.0000 - tn: 29.0000 - fn: 12.0000 - accuracy: 0.6724 - precision: 0.5882 - recall: 0.4545 - auc: 0.6616 - prc: 0.5851 - val_loss: 1.2353 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5963 - val_prc: 0.6506
Epoch 48/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6673 - tp: 5.0000 - fp: 6.0000 - tn: 30.0000 - fn: 17.0000 - accuracy: 0.6034 - precision: 0.4545 - recall: 0.2273 - auc: 0.5587 - prc: 0.4591 - val_loss: 0.6620 - val_tp: 5.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 4.0000 - val_accuracy: 0.5000 - val_precision: 0.3846 - val_recall: 0.5556 - val_auc: 0.6741 - val_prc: 0.6882
Epoch 49/150
29/29 [==============================] - 5s 178ms/step - loss: 0.6260 - tp: 5.0000 - fp: 5.0000 - tn: 31.0000 - fn: 17.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2273 - auc: 0.6515 - prc: 0.4895 - val_loss: 0.6224 - val_tp: 6.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 3.0000 - val_accuracy: 0.7500 - val_precision: 0.6667 - val_recall: 0.6667 - val_auc: 0.7000 - val_prc: 0.5446
Epoch 50/150
29/29 [==============================] - 5s 177ms/step - loss: 0.5576 - tp: 8.0000 - fp: 4.0000 - tn: 32.0000 - fn: 14.0000 - accuracy: 0.6897 - precision: 0.6667 - recall: 0.3636 - auc: 0.7809 - prc: 0.7074 - val_loss: 0.6304 - val_tp: 4.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 5.0000 - val_accuracy: 0.7083 - val_precision: 0.6667 - val_recall: 0.4444 - val_auc: 0.6444 - val_prc: 0.5080
Epoch 51/150
29/29 [==============================] - 6s 201ms/step - loss: 0.5758 - tp: 6.0000 - fp: 7.0000 - tn: 29.0000 - fn: 16.0000 - accuracy: 0.6034 - precision: 0.4615 - recall: 0.2727 - auc: 0.7443 - prc: 0.5919 - val_loss: 0.5417 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.7481 - val_prc: 0.6548
Epoch 52/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6394 - tp: 11.0000 - fp: 10.0000 - tn: 26.0000 - fn: 11.0000 - accuracy: 0.6379 - precision: 0.5238 - recall: 0.5000 - auc: 0.6313 - prc: 0.5428 - val_loss: 0.8636 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.7407 - val_prc: 0.6544
Epoch 53/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5710 - tp: 11.0000 - fp: 5.0000 - tn: 31.0000 - fn: 11.0000 - accuracy: 0.7241 - precision: 0.6875 - recall: 0.5000 - auc: 0.7614 - prc: 0.6236 - val_loss: 0.5986 - val_tp: 6.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 3.0000 - val_accuracy: 0.7083 - val_precision: 0.6000 - val_recall: 0.6667 - val_auc: 0.7704 - val_prc: 0.6903
Epoch 54/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6205 - tp: 8.0000 - fp: 9.0000 - tn: 27.0000 - fn: 14.0000 - accuracy: 0.6034 - precision: 0.4706 - recall: 0.3636 - auc: 0.6597 - prc: 0.5286 - val_loss: 0.6661 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7926 - val_prc: 0.7478
Epoch 55/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6115 - tp: 8.0000 - fp: 8.0000 - tn: 28.0000 - fn: 14.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.3636 - auc: 0.6881 - prc: 0.5360 - val_loss: 0.6422 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.7741 - val_prc: 0.7251
Epoch 56/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5945 - tp: 10.0000 - fp: 9.0000 - tn: 27.0000 - fn: 12.0000 - accuracy: 0.6379 - precision: 0.5263 - recall: 0.4545 - auc: 0.7146 - prc: 0.5257 - val_loss: 0.8486 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.6852 - val_prc: 0.5973
Epoch 57/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6536 - tp: 9.0000 - fp: 8.0000 - tn: 28.0000 - fn: 13.0000 - accuracy: 0.6379 - precision: 0.5294 - recall: 0.4091 - auc: 0.6143 - prc: 0.5606 - val_loss: 0.8299 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7630 - val_prc: 0.5696
Epoch 58/150
29/29 [==============================] - 5s 178ms/step - loss: 0.5820 - tp: 11.0000 - fp: 7.0000 - tn: 29.0000 - fn: 11.0000 - accuracy: 0.6897 - precision: 0.6111 - recall: 0.5000 - auc: 0.7412 - prc: 0.5989 - val_loss: 0.8487 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.7926 - val_prc: 0.7304
Epoch 59/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5255 - tp: 14.0000 - fp: 8.0000 - tn: 28.0000 - fn: 8.0000 - accuracy: 0.7241 - precision: 0.6364 - recall: 0.6364 - auc: 0.8024 - prc: 0.6227 - val_loss: 1.0695 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.7667 - val_prc: 0.6272
Epoch 60/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5907 - tp: 11.0000 - fp: 8.0000 - tn: 28.0000 - fn: 11.0000 - accuracy: 0.6724 - precision: 0.5789 - recall: 0.5000 - auc: 0.7140 - prc: 0.5619 - val_loss: 0.9581 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.7333 - val_prc: 0.5601
Epoch 61/150
29/29 [==============================] - 6s 203ms/step - loss: 0.6408 - tp: 7.0000 - fp: 10.0000 - tn: 26.0000 - fn: 15.0000 - accuracy: 0.5690 - precision: 0.4118 - recall: 0.3182 - auc: 0.6326 - prc: 0.4991 - val_loss: 0.7301 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.7407 - val_prc: 0.5834
Epoch 62/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6845 - tp: 6.0000 - fp: 8.0000 - tn: 28.0000 - fn: 16.0000 - accuracy: 0.5862 - precision: 0.4286 - recall: 0.2727 - auc: 0.5713 - prc: 0.4162 - val_loss: 0.5686 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.7815 - val_prc: 0.7189
Epoch 63/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6058 - tp: 11.0000 - fp: 4.0000 - tn: 32.0000 - fn: 11.0000 - accuracy: 0.7414 - precision: 0.7333 - recall: 0.5000 - auc: 0.7096 - prc: 0.6545 - val_loss: 0.6273 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.6444 - val_prc: 0.4692
Epoch 64/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5758 - tp: 10.0000 - fp: 7.0000 - tn: 29.0000 - fn: 12.0000 - accuracy: 0.6724 - precision: 0.5882 - recall: 0.4545 - auc: 0.7443 - prc: 0.5750 - val_loss: 0.5612 - val_tp: 6.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 3.0000 - val_accuracy: 0.6667 - val_precision: 0.5455 - val_recall: 0.6667 - val_auc: 0.7852 - val_prc: 0.6986
Epoch 65/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5364 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8043 - prc: 0.7823 - val_loss: 0.7267 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7815 - val_prc: 0.7058
Epoch 66/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5138 - tp: 10.0000 - fp: 4.0000 - tn: 32.0000 - fn: 12.0000 - accuracy: 0.7241 - precision: 0.7143 - recall: 0.4545 - auc: 0.8258 - prc: 0.7563 - val_loss: 0.8425 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7926 - val_prc: 0.6857
Epoch 67/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6064 - tp: 10.0000 - fp: 5.0000 - tn: 31.0000 - fn: 12.0000 - accuracy: 0.7069 - precision: 0.6667 - recall: 0.4545 - auc: 0.7020 - prc: 0.6413 - val_loss: 1.0756 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.7630 - val_prc: 0.6048
Epoch 68/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4752 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.8586 - prc: 0.8092 - val_loss: 0.5514 - val_tp: 8.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 1.0000 - val_accuracy: 0.7083 - val_precision: 0.5714 - val_recall: 0.8889 - val_auc: 0.7778 - val_prc: 0.6908
Epoch 69/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5680 - tp: 7.0000 - fp: 6.0000 - tn: 30.0000 - fn: 15.0000 - accuracy: 0.6379 - precision: 0.5385 - recall: 0.3182 - auc: 0.7601 - prc: 0.6544 - val_loss: 0.7441 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7778 - val_prc: 0.6757
Epoch 70/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5528 - tp: 14.0000 - fp: 11.0000 - tn: 25.0000 - fn: 8.0000 - accuracy: 0.6724 - precision: 0.5600 - recall: 0.6364 - auc: 0.7620 - prc: 0.6741 - val_loss: 0.7975 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.8222 - val_prc: 0.7165
Epoch 71/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6495 - tp: 8.0000 - fp: 10.0000 - tn: 26.0000 - fn: 14.0000 - accuracy: 0.5862 - precision: 0.4444 - recall: 0.3636 - auc: 0.6433 - prc: 0.4926 - val_loss: 0.5878 - val_tp: 6.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 3.0000 - val_accuracy: 0.7500 - val_precision: 0.6667 - val_recall: 0.6667 - val_auc: 0.7630 - val_prc: 0.6391
Epoch 72/150
29/29 [==============================] - 6s 202ms/step - loss: 0.5368 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.7986 - prc: 0.7753 - val_loss: 0.6693 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.8222 - val_prc: 0.7316
Epoch 73/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5834 - tp: 8.0000 - fp: 5.0000 - tn: 31.0000 - fn: 14.0000 - accuracy: 0.6724 - precision: 0.6154 - recall: 0.3636 - auc: 0.7109 - prc: 0.6415 - val_loss: 0.8784 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7852 - val_prc: 0.6437
Epoch 74/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5698 - tp: 9.0000 - fp: 5.0000 - tn: 31.0000 - fn: 13.0000 - accuracy: 0.6897 - precision: 0.6429 - recall: 0.4091 - auc: 0.7380 - prc: 0.6186 - val_loss: 0.7223 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7852 - val_prc: 0.6321
Epoch 75/150
29/29 [==============================] - 5s 185ms/step - loss: 0.5552 - tp: 9.0000 - fp: 3.0000 - tn: 33.0000 - fn: 13.0000 - accuracy: 0.7241 - precision: 0.7500 - recall: 0.4091 - auc: 0.7677 - prc: 0.6878 - val_loss: 0.5878 - val_tp: 9.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7083 - val_precision: 0.5625 - val_recall: 1.0000 - val_auc: 0.8296 - val_prc: 0.7571
Epoch 76/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6154 - tp: 6.0000 - fp: 8.0000 - tn: 28.0000 - fn: 16.0000 - accuracy: 0.5862 - precision: 0.4286 - recall: 0.2727 - auc: 0.6667 - prc: 0.5832 - val_loss: 1.0197 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.8074 - val_prc: 0.6452
Epoch 77/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4835 - tp: 15.0000 - fp: 7.0000 - tn: 29.0000 - fn: 7.0000 - accuracy: 0.7586 - precision: 0.6818 - recall: 0.6818 - auc: 0.8712 - prc: 0.8272 - val_loss: 0.7506 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7519 - val_prc: 0.5957
Epoch 78/150
29/29 [==============================] - 5s 181ms/step - loss: 0.4491 - tp: 17.0000 - fp: 6.0000 - tn: 30.0000 - fn: 5.0000 - accuracy: 0.8103 - precision: 0.7391 - recall: 0.7727 - auc: 0.8838 - prc: 0.8397 - val_loss: 0.5670 - val_tp: 8.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 1.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.8889 - val_auc: 0.8333 - val_prc: 0.8122
Epoch 79/150
29/29 [==============================] - 6s 203ms/step - loss: 0.6433 - tp: 8.0000 - fp: 8.0000 - tn: 28.0000 - fn: 14.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.3636 - auc: 0.6244 - prc: 0.5385 - val_loss: 0.7280 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7370 - val_prc: 0.5898
Epoch 80/150
29/29 [==============================] - 5s 177ms/step - loss: 0.4756 - tp: 14.0000 - fp: 6.0000 - tn: 30.0000 - fn: 8.0000 - accuracy: 0.7586 - precision: 0.7000 - recall: 0.6364 - auc: 0.8491 - prc: 0.7622 - val_loss: 0.9462 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7444 - val_prc: 0.5806
Epoch 81/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5501 - tp: 15.0000 - fp: 6.0000 - tn: 30.0000 - fn: 7.0000 - accuracy: 0.7759 - precision: 0.7143 - recall: 0.6818 - auc: 0.7677 - prc: 0.7080 - val_loss: 0.7317 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7259 - val_prc: 0.5787
Epoch 82/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5671 - tp: 12.0000 - fp: 7.0000 - tn: 29.0000 - fn: 10.0000 - accuracy: 0.7069 - precision: 0.6316 - recall: 0.5455 - auc: 0.7633 - prc: 0.6235 - val_loss: 0.6504 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.7222 - val_prc: 0.5968
Epoch 83/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5685 - tp: 12.0000 - fp: 11.0000 - tn: 25.0000 - fn: 10.0000 - accuracy: 0.6379 - precision: 0.5217 - recall: 0.5455 - auc: 0.7348 - prc: 0.5781 - val_loss: 0.5893 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.7407 - val_prc: 0.5896
Epoch 84/150
29/29 [==============================] - 5s 180ms/step - loss: 0.4972 - tp: 17.0000 - fp: 6.0000 - tn: 30.0000 - fn: 5.0000 - accuracy: 0.8103 - precision: 0.7391 - recall: 0.7727 - auc: 0.8371 - prc: 0.7867 - val_loss: 0.5521 - val_tp: 4.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 5.0000 - val_accuracy: 0.6667 - val_precision: 0.5714 - val_recall: 0.4444 - val_auc: 0.7407 - val_prc: 0.5887
Epoch 85/150
29/29 [==============================] - 5s 180ms/step - loss: 0.5048 - tp: 12.0000 - fp: 2.0000 - tn: 34.0000 - fn: 10.0000 - accuracy: 0.7931 - precision: 0.8571 - recall: 0.5455 - auc: 0.8346 - prc: 0.8221 - val_loss: 0.6126 - val_tp: 8.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 1.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.8889 - val_auc: 0.7333 - val_prc: 0.6328
Epoch 86/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4749 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.8554 - prc: 0.8553 - val_loss: 0.5405 - val_tp: 4.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 5.0000 - val_accuracy: 0.7083 - val_precision: 0.6667 - val_recall: 0.4444 - val_auc: 0.7519 - val_prc: 0.6317
Epoch 87/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4594 - tp: 13.0000 - fp: 4.0000 - tn: 32.0000 - fn: 9.0000 - accuracy: 0.7759 - precision: 0.7647 - recall: 0.5909 - auc: 0.8636 - prc: 0.8104 - val_loss: 0.5732 - val_tp: 5.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 4.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.5556 - val_auc: 0.7704 - val_prc: 0.6328
Epoch 88/150
29/29 [==============================] - 5s 180ms/step - loss: 0.4853 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.8422 - prc: 0.7794 - val_loss: 0.6447 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.7111 - val_prc: 0.6129
Epoch 89/150
29/29 [==============================] - 6s 204ms/step - loss: 0.4654 - tp: 13.0000 - fp: 6.0000 - tn: 30.0000 - fn: 9.0000 - accuracy: 0.7414 - precision: 0.6842 - recall: 0.5909 - auc: 0.8529 - prc: 0.7959 - val_loss: 0.5588 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.7556 - val_prc: 0.5767
Epoch 90/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5127 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.8207 - prc: 0.8025 - val_loss: 0.5891 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.7259 - val_prc: 0.5909
Epoch 91/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4447 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.8744 - prc: 0.8160 - val_loss: 0.9514 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7370 - val_prc: 0.5892
Epoch 92/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4973 - tp: 12.0000 - fp: 6.0000 - tn: 30.0000 - fn: 10.0000 - accuracy: 0.7241 - precision: 0.6667 - recall: 0.5455 - auc: 0.8093 - prc: 0.7440 - val_loss: 0.7238 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.8222 - val_prc: 0.6338
Epoch 93/150
29/29 [==============================] - 5s 181ms/step - loss: 0.4992 - tp: 13.0000 - fp: 6.0000 - tn: 30.0000 - fn: 9.0000 - accuracy: 0.7414 - precision: 0.6842 - recall: 0.5909 - auc: 0.8213 - prc: 0.7252 - val_loss: 0.5491 - val_tp: 6.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 3.0000 - val_accuracy: 0.7083 - val_precision: 0.6000 - val_recall: 0.6667 - val_auc: 0.7741 - val_prc: 0.6171
Epoch 94/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4720 - tp: 11.0000 - fp: 2.0000 - tn: 34.0000 - fn: 11.0000 - accuracy: 0.7759 - precision: 0.8462 - recall: 0.5000 - auc: 0.8327 - prc: 0.8080 - val_loss: 0.7878 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7778 - val_prc: 0.6203
Epoch 95/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4566 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.8516 - prc: 0.7921 - val_loss: 0.8299 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7444 - val_prc: 0.5831
Epoch 96/150
29/29 [==============================] - 6s 203ms/step - loss: 0.3962 - tp: 18.0000 - fp: 3.0000 - tn: 33.0000 - fn: 4.0000 - accuracy: 0.8793 - precision: 0.8571 - recall: 0.8182 - auc: 0.9205 - prc: 0.8865 - val_loss: 0.6900 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.7407 - val_prc: 0.5802
Epoch 97/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4767 - tp: 16.0000 - fp: 8.0000 - tn: 28.0000 - fn: 6.0000 - accuracy: 0.7586 - precision: 0.6667 - recall: 0.7273 - auc: 0.8314 - prc: 0.7729 - val_loss: 0.9409 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7630 - val_prc: 0.5902
Epoch 98/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5089 - tp: 13.0000 - fp: 6.0000 - tn: 30.0000 - fn: 9.0000 - accuracy: 0.7414 - precision: 0.6842 - recall: 0.5909 - auc: 0.8068 - prc: 0.7213 - val_loss: 0.7647 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7926 - val_prc: 0.6194
Epoch 99/150
29/29 [==============================] - 5s 183ms/step - loss: 0.3814 - tp: 18.0000 - fp: 3.0000 - tn: 33.0000 - fn: 4.0000 - accuracy: 0.8793 - precision: 0.8571 - recall: 0.8182 - auc: 0.9211 - prc: 0.8757 - val_loss: 0.6917 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7630 - val_prc: 0.5997
Epoch 100/150
29/29 [==============================] - 5s 180ms/step - loss: 0.4576 - tp: 14.0000 - fp: 7.0000 - tn: 29.0000 - fn: 8.0000 - accuracy: 0.7414 - precision: 0.6667 - recall: 0.6364 - auc: 0.8403 - prc: 0.7991 - val_loss: 0.5468 - val_tp: 7.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 2.0000 - val_accuracy: 0.7083 - val_precision: 0.5833 - val_recall: 0.7778 - val_auc: 0.7926 - val_prc: 0.6373
Epoch 101/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4992 - tp: 10.0000 - fp: 6.0000 - tn: 30.0000 - fn: 12.0000 - accuracy: 0.6897 - precision: 0.6250 - recall: 0.4545 - auc: 0.8150 - prc: 0.6876 - val_loss: 0.5874 - val_tp: 9.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7917 - val_precision: 0.6429 - val_recall: 1.0000 - val_auc: 0.7963 - val_prc: 0.6272
Epoch 102/150
29/29 [==============================] - 5s 182ms/step - loss: 0.3978 - tp: 16.0000 - fp: 5.0000 - tn: 31.0000 - fn: 6.0000 - accuracy: 0.8103 - precision: 0.7619 - recall: 0.7273 - auc: 0.8971 - prc: 0.8646 - val_loss: 0.5416 - val_tp: 9.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7083 - val_precision: 0.5625 - val_recall: 1.0000 - val_auc: 0.8481 - val_prc: 0.7233
Epoch 103/150
29/29 [==============================] - 6s 203ms/step - loss: 0.3225 - tp: 20.0000 - fp: 4.0000 - tn: 32.0000 - fn: 2.0000 - accuracy: 0.8966 - precision: 0.8333 - recall: 0.9091 - auc: 0.9508 - prc: 0.9096 - val_loss: 0.6056 - val_tp: 9.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7500 - val_precision: 0.6000 - val_recall: 1.0000 - val_auc: 0.8111 - val_prc: 0.6288
Epoch 104/150
29/29 [==============================] - 5s 177ms/step - loss: 0.4978 - tp: 14.0000 - fp: 7.0000 - tn: 29.0000 - fn: 8.0000 - accuracy: 0.7414 - precision: 0.6667 - recall: 0.6364 - auc: 0.8169 - prc: 0.7811 - val_loss: 0.5363 - val_tp: 2.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 7.0000 - val_accuracy: 0.5833 - val_precision: 0.4000 - val_recall: 0.2222 - val_auc: 0.8259 - val_prc: 0.6409
Epoch 105/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4204 - tp: 17.0000 - fp: 7.0000 - tn: 29.0000 - fn: 5.0000 - accuracy: 0.7931 - precision: 0.7083 - recall: 0.7727 - auc: 0.8920 - prc: 0.8506 - val_loss: 0.7022 - val_tp: 8.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 1.0000 - val_accuracy: 0.7917 - val_precision: 0.6667 - val_recall: 0.8889 - val_auc: 0.7852 - val_prc: 0.6055
Epoch 106/150
29/29 [==============================] - 5s 178ms/step - loss: 0.4013 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8984 - prc: 0.8537 - val_loss: 0.6417 - val_tp: 4.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 5.0000 - val_accuracy: 0.6667 - val_precision: 0.5714 - val_recall: 0.4444 - val_auc: 0.8074 - val_prc: 0.6291
Epoch 107/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4677 - tp: 15.0000 - fp: 7.0000 - tn: 29.0000 - fn: 7.0000 - accuracy: 0.7586 - precision: 0.6818 - recall: 0.6818 - auc: 0.8403 - prc: 0.7835 - val_loss: 0.7031 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.7556 - val_prc: 0.5980
Epoch 108/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4087 - tp: 17.0000 - fp: 7.0000 - tn: 29.0000 - fn: 5.0000 - accuracy: 0.7931 - precision: 0.7083 - recall: 0.7727 - auc: 0.8965 - prc: 0.8407 - val_loss: 0.5617 - val_tp: 7.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 2.0000 - val_accuracy: 0.7083 - val_precision: 0.5833 - val_recall: 0.7778 - val_auc: 0.7704 - val_prc: 0.6275
Epoch 109/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3948 - tp: 18.0000 - fp: 7.0000 - tn: 29.0000 - fn: 4.0000 - accuracy: 0.8103 - precision: 0.7200 - recall: 0.8182 - auc: 0.9141 - prc: 0.8720 - val_loss: 0.7229 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7926 - val_prc: 0.6126
Epoch 110/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4375 - tp: 15.0000 - fp: 3.0000 - tn: 33.0000 - fn: 7.0000 - accuracy: 0.8276 - precision: 0.8333 - recall: 0.6818 - auc: 0.8712 - prc: 0.8051 - val_loss: 0.9132 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7963 - val_prc: 0.5592
Epoch 111/150
29/29 [==============================] - 6s 204ms/step - loss: 0.4325 - tp: 14.0000 - fp: 4.0000 - tn: 32.0000 - fn: 8.0000 - accuracy: 0.7931 - precision: 0.7778 - recall: 0.6364 - auc: 0.8725 - prc: 0.8424 - val_loss: 0.7350 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.7519 - val_prc: 0.5969
Epoch 112/150
29/29 [==============================] - 6s 206ms/step - loss: 0.3652 - tp: 18.0000 - fp: 3.0000 - tn: 33.0000 - fn: 4.0000 - accuracy: 0.8793 - precision: 0.8571 - recall: 0.8182 - auc: 0.9173 - prc: 0.8903 - val_loss: 0.7394 - val_tp: 9.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7917 - val_precision: 0.6429 - val_recall: 1.0000 - val_auc: 0.8148 - val_prc: 0.5568
Epoch 113/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3341 - tp: 18.0000 - fp: 3.0000 - tn: 33.0000 - fn: 4.0000 - accuracy: 0.8793 - precision: 0.8571 - recall: 0.8182 - auc: 0.9318 - prc: 0.8883 - val_loss: 0.7916 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.8074 - val_prc: 0.5688
Epoch 114/150
29/29 [==============================] - 6s 204ms/step - loss: 0.3653 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.9129 - prc: 0.8670 - val_loss: 0.5830 - val_tp: 9.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7917 - val_precision: 0.6429 - val_recall: 1.0000 - val_auc: 0.8259 - val_prc: 0.6409
Epoch 115/150
29/29 [==============================] - 5s 179ms/step - loss: 0.4516 - tp: 14.0000 - fp: 7.0000 - tn: 29.0000 - fn: 8.0000 - accuracy: 0.7414 - precision: 0.6667 - recall: 0.6364 - auc: 0.8573 - prc: 0.8112 - val_loss: 0.9753 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7556 - val_prc: 0.5279
Epoch 116/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3821 - tp: 15.0000 - fp: 2.0000 - tn: 34.0000 - fn: 7.0000 - accuracy: 0.8448 - precision: 0.8824 - recall: 0.6818 - auc: 0.9217 - prc: 0.8727 - val_loss: 0.8852 - val_tp: 7.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 2.0000 - val_accuracy: 0.5417 - val_precision: 0.4375 - val_recall: 0.7778 - val_auc: 0.7111 - val_prc: 0.5018
Epoch 117/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3503 - tp: 19.0000 - fp: 6.0000 - tn: 30.0000 - fn: 3.0000 - accuracy: 0.8448 - precision: 0.7600 - recall: 0.8636 - auc: 0.9312 - prc: 0.9195 - val_loss: 0.8045 - val_tp: 7.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 2.0000 - val_accuracy: 0.7917 - val_precision: 0.7000 - val_recall: 0.7778 - val_auc: 0.6778 - val_prc: 0.4830
Epoch 118/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3895 - tp: 15.0000 - fp: 2.0000 - tn: 34.0000 - fn: 7.0000 - accuracy: 0.8448 - precision: 0.8824 - recall: 0.6818 - auc: 0.9034 - prc: 0.8964 - val_loss: 0.6635 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.7556 - val_prc: 0.6040
Epoch 119/150
29/29 [==============================] - 5s 186ms/step - loss: 0.5087 - tp: 12.0000 - fp: 10.0000 - tn: 26.0000 - fn: 10.0000 - accuracy: 0.6552 - precision: 0.5455 - recall: 0.5455 - auc: 0.7948 - prc: 0.7226 - val_loss: 0.6657 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.8000 - val_prc: 0.5502
Epoch 120/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2348 - tp: 21.0000 - fp: 2.0000 - tn: 34.0000 - fn: 1.0000 - accuracy: 0.9483 - precision: 0.9130 - recall: 0.9545 - auc: 0.9798 - prc: 0.9608 - val_loss: 0.5682 - val_tp: 4.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 5.0000 - val_accuracy: 0.6667 - val_precision: 0.5714 - val_recall: 0.4444 - val_auc: 0.7778 - val_prc: 0.6127
Epoch 121/150
29/29 [==============================] - 5s 183ms/step - loss: 0.3735 - tp: 17.0000 - fp: 5.0000 - tn: 31.0000 - fn: 5.0000 - accuracy: 0.8276 - precision: 0.7727 - recall: 0.7727 - auc: 0.9097 - prc: 0.8467 - val_loss: 0.5960 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7222 - val_prc: 0.6640
Epoch 122/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3904 - tp: 18.0000 - fp: 4.0000 - tn: 32.0000 - fn: 4.0000 - accuracy: 0.8621 - precision: 0.8182 - recall: 0.8182 - auc: 0.9059 - prc: 0.8604 - val_loss: 0.7521 - val_tp: 7.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 2.0000 - val_accuracy: 0.7917 - val_precision: 0.7000 - val_recall: 0.7778 - val_auc: 0.8074 - val_prc: 0.5730
Epoch 123/150
29/29 [==============================] - 5s 184ms/step - loss: 0.4307 - tp: 13.0000 - fp: 4.0000 - tn: 32.0000 - fn: 9.0000 - accuracy: 0.7759 - precision: 0.7647 - recall: 0.5909 - auc: 0.8662 - prc: 0.8304 - val_loss: 0.8221 - val_tp: 8.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 1.0000 - val_accuracy: 0.7500 - val_precision: 0.6154 - val_recall: 0.8889 - val_auc: 0.7815 - val_prc: 0.5605
Epoch 124/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3608 - tp: 15.0000 - fp: 4.0000 - tn: 32.0000 - fn: 7.0000 - accuracy: 0.8103 - precision: 0.7895 - recall: 0.6818 - auc: 0.9173 - prc: 0.8897 - val_loss: 0.6435 - val_tp: 3.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 6.0000 - val_accuracy: 0.6667 - val_precision: 0.6000 - val_recall: 0.3333 - val_auc: 0.7963 - val_prc: 0.6412
Epoch 125/150
29/29 [==============================] - 6s 204ms/step - loss: 0.4595 - tp: 12.0000 - fp: 7.0000 - tn: 29.0000 - fn: 10.0000 - accuracy: 0.7069 - precision: 0.6316 - recall: 0.5455 - auc: 0.8510 - prc: 0.8111 - val_loss: 0.5586 - val_tp: 7.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 2.0000 - val_accuracy: 0.7917 - val_precision: 0.7000 - val_recall: 0.7778 - val_auc: 0.8444 - val_prc: 0.6860
Epoch 126/150
29/29 [==============================] - 5s 179ms/step - loss: 0.5282 - tp: 14.0000 - fp: 6.0000 - tn: 30.0000 - fn: 8.0000 - accuracy: 0.7586 - precision: 0.7000 - recall: 0.6364 - auc: 0.7973 - prc: 0.7196 - val_loss: 0.5984 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.8444 - val_prc: 0.6145
Epoch 127/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2486 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9823 - prc: 0.9752 - val_loss: 0.5118 - val_tp: 5.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 4.0000 - val_accuracy: 0.7500 - val_precision: 0.7143 - val_recall: 0.5556 - val_auc: 0.8296 - val_prc: 0.6650
Epoch 128/150
29/29 [==============================] - 5s 184ms/step - loss: 0.3434 - tp: 18.0000 - fp: 4.0000 - tn: 32.0000 - fn: 4.0000 - accuracy: 0.8621 - precision: 0.8182 - recall: 0.8182 - auc: 0.9261 - prc: 0.9242 - val_loss: 0.8890 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.8519 - val_prc: 0.6766
Epoch 129/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3145 - tp: 18.0000 - fp: 4.0000 - tn: 32.0000 - fn: 4.0000 - accuracy: 0.8621 - precision: 0.8182 - recall: 0.8182 - auc: 0.9457 - prc: 0.9302 - val_loss: 0.7309 - val_tp: 9.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7917 - val_precision: 0.6429 - val_recall: 1.0000 - val_auc: 0.8296 - val_prc: 0.5784
Epoch 130/150
29/29 [==============================] - 6s 205ms/step - loss: 0.3860 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.9040 - prc: 0.8792 - val_loss: 0.7924 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7741 - val_prc: 0.6130
Epoch 131/150
29/29 [==============================] - 5s 182ms/step - loss: 0.3228 - tp: 16.0000 - fp: 3.0000 - tn: 33.0000 - fn: 6.0000 - accuracy: 0.8448 - precision: 0.8421 - recall: 0.7273 - auc: 0.9337 - prc: 0.9099 - val_loss: 0.5971 - val_tp: 4.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 5.0000 - val_accuracy: 0.7083 - val_precision: 0.6667 - val_recall: 0.4444 - val_auc: 0.7630 - val_prc: 0.6222
Epoch 132/150
29/29 [==============================] - 5s 181ms/step - loss: 0.4218 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.8788 - prc: 0.8136 - val_loss: 0.5367 - val_tp: 6.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 3.0000 - val_accuracy: 0.6667 - val_precision: 0.5455 - val_recall: 0.6667 - val_auc: 0.7704 - val_prc: 0.5306
Epoch 133/150
29/29 [==============================] - 5s 183ms/step - loss: 0.3656 - tp: 17.0000 - fp: 5.0000 - tn: 31.0000 - fn: 5.0000 - accuracy: 0.8276 - precision: 0.7727 - recall: 0.7727 - auc: 0.9078 - prc: 0.8838 - val_loss: 0.9682 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.8074 - val_prc: 0.5502
Epoch 134/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3243 - tp: 17.0000 - fp: 3.0000 - tn: 33.0000 - fn: 5.0000 - accuracy: 0.8621 - precision: 0.8500 - recall: 0.7727 - auc: 0.9426 - prc: 0.9233 - val_loss: 1.0982 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.7074 - val_prc: 0.4750
Epoch 135/150
29/29 [==============================] - 6s 205ms/step - loss: 0.3823 - tp: 15.0000 - fp: 6.0000 - tn: 30.0000 - fn: 7.0000 - accuracy: 0.7759 - precision: 0.7143 - recall: 0.6818 - auc: 0.9015 - prc: 0.8525 - val_loss: 0.6301 - val_tp: 6.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 3.0000 - val_accuracy: 0.7500 - val_precision: 0.6667 - val_recall: 0.6667 - val_auc: 0.7556 - val_prc: 0.5358
Epoch 136/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3087 - tp: 19.0000 - fp: 6.0000 - tn: 30.0000 - fn: 3.0000 - accuracy: 0.8448 - precision: 0.7600 - recall: 0.8636 - auc: 0.9457 - prc: 0.9215 - val_loss: 0.6437 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.7444 - val_prc: 0.6089
Epoch 137/150
29/29 [==============================] - 5s 182ms/step - loss: 0.2735 - tp: 19.0000 - fp: 3.0000 - tn: 33.0000 - fn: 3.0000 - accuracy: 0.8966 - precision: 0.8636 - recall: 0.8636 - auc: 0.9602 - prc: 0.9406 - val_loss: 0.7527 - val_tp: 8.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 1.0000 - val_accuracy: 0.6667 - val_precision: 0.5333 - val_recall: 0.8889 - val_auc: 0.7407 - val_prc: 0.5234
Epoch 138/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3350 - tp: 15.0000 - fp: 3.0000 - tn: 33.0000 - fn: 7.0000 - accuracy: 0.8276 - precision: 0.8333 - recall: 0.6818 - auc: 0.9318 - prc: 0.8967 - val_loss: 1.2845 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.6778 - val_prc: 0.4751
Epoch 139/150
29/29 [==============================] - 5s 181ms/step - loss: 0.2660 - tp: 20.0000 - fp: 4.0000 - tn: 32.0000 - fn: 2.0000 - accuracy: 0.8966 - precision: 0.8333 - recall: 0.9091 - auc: 0.9634 - prc: 0.9440 - val_loss: 1.0685 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7519 - val_prc: 0.5315
Epoch 140/150
29/29 [==============================] - 5s 180ms/step - loss: 0.3174 - tp: 17.0000 - fp: 1.0000 - tn: 35.0000 - fn: 5.0000 - accuracy: 0.8966 - precision: 0.9444 - recall: 0.7727 - auc: 0.9362 - prc: 0.9181 - val_loss: 0.5186 - val_tp: 9.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.7500 - val_precision: 0.6000 - val_recall: 1.0000 - val_auc: 0.8185 - val_prc: 0.6623
Epoch 141/150
29/29 [==============================] - 5s 184ms/step - loss: 0.2520 - tp: 21.0000 - fp: 3.0000 - tn: 33.0000 - fn: 1.0000 - accuracy: 0.9310 - precision: 0.8750 - recall: 0.9545 - auc: 0.9691 - prc: 0.9353 - val_loss: 0.5983 - val_tp: 6.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 3.0000 - val_accuracy: 0.7083 - val_precision: 0.6000 - val_recall: 0.6667 - val_auc: 0.7815 - val_prc: 0.5590
Epoch 142/150
29/29 [==============================] - 5s 181ms/step - loss: 0.2707 - tp: 17.0000 - fp: 2.0000 - tn: 34.0000 - fn: 5.0000 - accuracy: 0.8793 - precision: 0.8947 - recall: 0.7727 - auc: 0.9672 - prc: 0.9555 - val_loss: 0.8502 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7741 - val_prc: 0.5509
Epoch 143/150
29/29 [==============================] - 5s 181ms/step - loss: 0.2451 - tp: 16.0000 - fp: 2.0000 - tn: 34.0000 - fn: 6.0000 - accuracy: 0.8621 - precision: 0.8889 - recall: 0.7273 - auc: 0.9602 - prc: 0.9489 - val_loss: 0.7822 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.8407 - val_prc: 0.5990
Epoch 144/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4054 - tp: 16.0000 - fp: 8.0000 - tn: 28.0000 - fn: 6.0000 - accuracy: 0.7586 - precision: 0.6667 - recall: 0.7273 - auc: 0.8838 - prc: 0.8657 - val_loss: 0.6807 - val_tp: 6.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 3.0000 - val_accuracy: 0.5833 - val_precision: 0.4615 - val_recall: 0.6667 - val_auc: 0.6593 - val_prc: 0.5073
Epoch 145/150
29/29 [==============================] - 5s 181ms/step - loss: 0.3129 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.9318 - prc: 0.9062 - val_loss: 1.0719 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7741 - val_prc: 0.5227
Epoch 146/150
29/29 [==============================] - 5s 184ms/step - loss: 0.2956 - tp: 19.0000 - fp: 1.0000 - tn: 35.0000 - fn: 3.0000 - accuracy: 0.9310 - precision: 0.9500 - recall: 0.8636 - auc: 0.9527 - prc: 0.9343 - val_loss: 0.8674 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.7519 - val_prc: 0.5146
Epoch 147/150
29/29 [==============================] - 5s 179ms/step - loss: 0.3469 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.9167 - prc: 0.8675 - val_loss: 1.3816 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7630 - val_prc: 0.5416
Epoch 148/150
29/29 [==============================] - 5s 180ms/step - loss: 0.2680 - tp: 18.0000 - fp: 4.0000 - tn: 32.0000 - fn: 4.0000 - accuracy: 0.8621 - precision: 0.8182 - recall: 0.8182 - auc: 0.9552 - prc: 0.9417 - val_loss: 0.6550 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.7704 - val_prc: 0.5871
Epoch 149/150
29/29 [==============================] - 5s 179ms/step - loss: 0.2699 - tp: 19.0000 - fp: 4.0000 - tn: 32.0000 - fn: 3.0000 - accuracy: 0.8793 - precision: 0.8261 - recall: 0.8636 - auc: 0.9640 - prc: 0.9416 - val_loss: 1.2333 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7778 - val_prc: 0.5428
Epoch 150/150
29/29 [==============================] - 5s 182ms/step - loss: 0.3789 - tp: 13.0000 - fp: 3.0000 - tn: 33.0000 - fn: 9.0000 - accuracy: 0.7931 - precision: 0.8125 - recall: 0.5909 - auc: 0.8977 - prc: 0.8600 - val_loss: 0.9867 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.8185 - val_prc: 0.5882
Advanced augmentation
The advanced approach is more aggressive since it includes zoom and even shear augmentation. As already specified, the latter also introduces an image distortion.
model = build_model(augmentation=True,
rotation=True,
flip=True,
shift=True,
zoom=True,
shear=True,
brightness=True,
contrast=True)
performance["advanced"] = train_model(model, training_dataset, validation_dataset)
WARNING:tensorflow:Using a while_loop for converting ImageProjectiveTransformV3 cause there is no registered converter for this op.
WARNING:tensorflow:Using a while_loop for converting ImageProjectiveTransformV3 cause there is no registered converter for this op.
Epoch 1/150
WARNING:tensorflow:Using a while_loop for converting ImageProjectiveTransformV3 cause there is no registered converter for this op.
WARNING:tensorflow:Using a while_loop for converting ImageProjectiveTransformV3 cause there is no registered converter for this op.
WARNING:tensorflow:Using a while_loop for converting ImageProjectiveTransformV3 cause there is no registered converter for this op.
WARNING:tensorflow:Using a while_loop for converting ImageProjectiveTransformV3 cause there is no registered converter for this op.
29/29 [==============================] - 12s 203ms/step - loss: 0.7046 - tp: 14.0000 - fp: 22.0000 - tn: 29.0000 - fn: 17.0000 - accuracy: 0.5244 - precision: 0.3889 - recall: 0.4516 - auc: 0.5427 - prc: 0.4471 - val_loss: 0.6764 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4222 - val_prc: 0.3302
Epoch 2/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6903 - tp: 2.0000 - fp: 7.0000 - tn: 29.0000 - fn: 20.0000 - accuracy: 0.5345 - precision: 0.2222 - recall: 0.0909 - auc: 0.4848 - prc: 0.3495 - val_loss: 0.7282 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5778 - val_prc: 0.4324
Epoch 3/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6244 - tp: 7.0000 - fp: 7.0000 - tn: 29.0000 - fn: 15.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.3182 - auc: 0.6578 - prc: 0.5596 - val_loss: 0.7974 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.3481 - val_prc: 0.3063
Epoch 4/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6840 - tp: 8.0000 - fp: 13.0000 - tn: 23.0000 - fn: 14.0000 - accuracy: 0.5345 - precision: 0.3810 - recall: 0.3636 - auc: 0.5644 - prc: 0.3948 - val_loss: 0.9454 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5000 - val_prc: 0.3750
Epoch 5/150
29/29 [==============================] - 5s 182ms/step - loss: 0.7390 - tp: 5.0000 - fp: 14.0000 - tn: 22.0000 - fn: 17.0000 - accuracy: 0.4655 - precision: 0.2632 - recall: 0.2273 - auc: 0.3977 - prc: 0.3196 - val_loss: 0.7560 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5926 - val_prc: 0.5165
Epoch 6/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6541 - tp: 6.0000 - fp: 2.0000 - tn: 34.0000 - fn: 16.0000 - accuracy: 0.6897 - precision: 0.7500 - recall: 0.2727 - auc: 0.6168 - prc: 0.5517 - val_loss: 0.8246 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6370 - val_prc: 0.5326
Epoch 7/150
29/29 [==============================] - 5s 182ms/step - loss: 0.7085 - tp: 6.0000 - fp: 13.0000 - tn: 23.0000 - fn: 16.0000 - accuracy: 0.5000 - precision: 0.3158 - recall: 0.2727 - auc: 0.4217 - prc: 0.3568 - val_loss: 0.6744 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6000 - val_prc: 0.5026
Epoch 8/150
29/29 [==============================] - 6s 205ms/step - loss: 0.6690 - tp: 2.0000 - fp: 4.0000 - tn: 32.0000 - fn: 20.0000 - accuracy: 0.5862 - precision: 0.3333 - recall: 0.0909 - auc: 0.5025 - prc: 0.3570 - val_loss: 0.7372 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.4074 - val_prc: 0.3063
Epoch 9/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6826 - tp: 2.0000 - fp: 2.0000 - tn: 34.0000 - fn: 20.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.0909 - auc: 0.4413 - prc: 0.4079 - val_loss: 0.6816 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5630 - val_prc: 0.5217
Epoch 10/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6951 - tp: 3.0000 - fp: 5.0000 - tn: 31.0000 - fn: 19.0000 - accuracy: 0.5862 - precision: 0.3750 - recall: 0.1364 - auc: 0.4463 - prc: 0.3494 - val_loss: 0.6639 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5926 - val_prc: 0.5852
Epoch 11/150
29/29 [==============================] - 6s 204ms/step - loss: 0.6829 - tp: 7.0000 - fp: 10.0000 - tn: 26.0000 - fn: 15.0000 - accuracy: 0.5690 - precision: 0.4118 - recall: 0.3182 - auc: 0.4943 - prc: 0.4054 - val_loss: 0.8546 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6037 - val_prc: 0.5473
Epoch 12/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6517 - tp: 2.0000 - fp: 3.0000 - tn: 33.0000 - fn: 20.0000 - accuracy: 0.6034 - precision: 0.4000 - recall: 0.0909 - auc: 0.5909 - prc: 0.4719 - val_loss: 0.8066 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5667 - val_prc: 0.5399
Epoch 13/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6674 - tp: 4.0000 - fp: 3.0000 - tn: 33.0000 - fn: 18.0000 - accuracy: 0.6379 - precision: 0.5714 - recall: 0.1818 - auc: 0.5366 - prc: 0.4593 - val_loss: 0.7085 - val_tp: 7.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 2.0000 - val_accuracy: 0.3750 - val_precision: 0.3500 - val_recall: 0.7778 - val_auc: 0.5111 - val_prc: 0.4115
Epoch 14/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6801 - tp: 4.0000 - fp: 3.0000 - tn: 33.0000 - fn: 18.0000 - accuracy: 0.6379 - precision: 0.5714 - recall: 0.1818 - auc: 0.4747 - prc: 0.3952 - val_loss: 0.6619 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5481 - val_prc: 0.4855
Epoch 15/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6520 - tp: 3.0000 - fp: 5.0000 - tn: 31.0000 - fn: 19.0000 - accuracy: 0.5862 - precision: 0.3750 - recall: 0.1364 - auc: 0.5846 - prc: 0.4373 - val_loss: 0.6975 - val_tp: 4.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 5.0000 - val_accuracy: 0.5000 - val_precision: 0.3636 - val_recall: 0.4444 - val_auc: 0.4741 - val_prc: 0.3648
Epoch 16/150
29/29 [==============================] - 6s 208ms/step - loss: 0.6187 - tp: 4.0000 - fp: 2.0000 - tn: 34.0000 - fn: 18.0000 - accuracy: 0.6552 - precision: 0.6667 - recall: 0.1818 - auc: 0.6926 - prc: 0.5912 - val_loss: 0.7353 - val_tp: 7.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 2.0000 - val_accuracy: 0.3333 - val_precision: 0.3333 - val_recall: 0.7778 - val_auc: 0.4667 - val_prc: 0.3716
Epoch 17/150
29/29 [==============================] - 6s 205ms/step - loss: 0.6701 - tp: 3.0000 - fp: 9.0000 - tn: 27.0000 - fn: 19.0000 - accuracy: 0.5172 - precision: 0.2500 - recall: 0.1364 - auc: 0.5297 - prc: 0.3845 - val_loss: 0.6876 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5519 - val_prc: 0.4178
Epoch 18/150
29/29 [==============================] - 6s 205ms/step - loss: 0.6775 - tp: 6.0000 - fp: 7.0000 - tn: 29.0000 - fn: 16.0000 - accuracy: 0.6034 - precision: 0.4615 - recall: 0.2727 - auc: 0.5638 - prc: 0.4825 - val_loss: 0.6814 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.5481 - val_prc: 0.4884
Epoch 19/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6564 - tp: 7.0000 - fp: 6.0000 - tn: 30.0000 - fn: 15.0000 - accuracy: 0.6379 - precision: 0.5385 - recall: 0.3182 - auc: 0.5909 - prc: 0.4990 - val_loss: 0.7657 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5481 - val_prc: 0.4780
Epoch 20/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6924 - tp: 8.0000 - fp: 12.0000 - tn: 24.0000 - fn: 14.0000 - accuracy: 0.5517 - precision: 0.4000 - recall: 0.3636 - auc: 0.5259 - prc: 0.4359 - val_loss: 0.7146 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.5593 - val_prc: 0.4812
Epoch 21/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6663 - tp: 2.0000 - fp: 3.0000 - tn: 33.0000 - fn: 20.0000 - accuracy: 0.6034 - precision: 0.4000 - recall: 0.0909 - auc: 0.5114 - prc: 0.4048 - val_loss: 0.6704 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.5370 - val_prc: 0.4039
Epoch 22/150
29/29 [==============================] - 5s 179ms/step - loss: 0.6685 - tp: 3.0000 - fp: 5.0000 - tn: 31.0000 - fn: 19.0000 - accuracy: 0.5862 - precision: 0.3750 - recall: 0.1364 - auc: 0.5739 - prc: 0.4351 - val_loss: 0.7108 - val_tp: 5.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 4.0000 - val_accuracy: 0.4583 - val_precision: 0.3571 - val_recall: 0.5556 - val_auc: 0.5037 - val_prc: 0.3629
Epoch 23/150
29/29 [==============================] - 5s 180ms/step - loss: 0.6624 - tp: 2.0000 - fp: 3.0000 - tn: 33.0000 - fn: 20.0000 - accuracy: 0.6034 - precision: 0.4000 - recall: 0.0909 - auc: 0.5404 - prc: 0.4075 - val_loss: 0.7205 - val_tp: 5.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 4.0000 - val_accuracy: 0.4167 - val_precision: 0.3333 - val_recall: 0.5556 - val_auc: 0.3963 - val_prc: 0.2977
Epoch 24/150
29/29 [==============================] - 6s 204ms/step - loss: 0.6372 - tp: 3.0000 - fp: 7.0000 - tn: 29.0000 - fn: 19.0000 - accuracy: 0.5517 - precision: 0.3000 - recall: 0.1364 - auc: 0.6288 - prc: 0.5001 - val_loss: 0.8073 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.6815 - val_prc: 0.6517
Epoch 25/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6473 - tp: 9.0000 - fp: 6.0000 - tn: 30.0000 - fn: 13.0000 - accuracy: 0.6724 - precision: 0.6000 - recall: 0.4091 - auc: 0.6288 - prc: 0.5083 - val_loss: 0.7682 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.6963 - val_prc: 0.6363
Epoch 26/150
29/29 [==============================] - 5s 186ms/step - loss: 0.6004 - tp: 5.0000 - fp: 5.0000 - tn: 31.0000 - fn: 17.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2273 - auc: 0.7027 - prc: 0.5617 - val_loss: 0.7955 - val_tp: 9.0000 - val_fp: 14.0000 - val_tn: 1.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4167 - val_precision: 0.3913 - val_recall: 1.0000 - val_auc: 0.7296 - val_prc: 0.6976
Epoch 27/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6501 - tp: 6.0000 - fp: 6.0000 - tn: 30.0000 - fn: 16.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2727 - auc: 0.6111 - prc: 0.4957 - val_loss: 1.1787 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.7259 - val_prc: 0.7172
Epoch 28/150
29/29 [==============================] - 5s 186ms/step - loss: 0.6617 - tp: 3.0000 - fp: 5.0000 - tn: 31.0000 - fn: 19.0000 - accuracy: 0.5862 - precision: 0.3750 - recall: 0.1364 - auc: 0.6080 - prc: 0.4269 - val_loss: 0.8681 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.7889 - val_prc: 0.7475
Epoch 29/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6911 - tp: 6.0000 - fp: 5.0000 - tn: 31.0000 - fn: 16.0000 - accuracy: 0.6379 - precision: 0.5455 - recall: 0.2727 - auc: 0.4918 - prc: 0.4204 - val_loss: 0.6744 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.7074 - val_prc: 0.6566
Epoch 30/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6421 - tp: 6.0000 - fp: 5.0000 - tn: 31.0000 - fn: 16.0000 - accuracy: 0.6379 - precision: 0.5455 - recall: 0.2727 - auc: 0.6263 - prc: 0.5563 - val_loss: 0.7569 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7148 - val_prc: 0.6154
Epoch 31/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6879 - tp: 2.0000 - fp: 3.0000 - tn: 33.0000 - fn: 20.0000 - accuracy: 0.6034 - precision: 0.4000 - recall: 0.0909 - auc: 0.4729 - prc: 0.3863 - val_loss: 0.6015 - val_tp: 5.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 4.0000 - val_accuracy: 0.6667 - val_precision: 0.5556 - val_recall: 0.5556 - val_auc: 0.7185 - val_prc: 0.6091
Epoch 32/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6516 - tp: 2.0000 - fp: 4.0000 - tn: 32.0000 - fn: 20.0000 - accuracy: 0.5862 - precision: 0.3333 - recall: 0.0909 - auc: 0.5884 - prc: 0.4562 - val_loss: 0.5953 - val_tp: 1.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 8.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.1111 - val_auc: 0.7333 - val_prc: 0.6369
Epoch 33/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6394 - tp: 8.0000 - fp: 9.0000 - tn: 27.0000 - fn: 14.0000 - accuracy: 0.6034 - precision: 0.4706 - recall: 0.3636 - auc: 0.6187 - prc: 0.5052 - val_loss: 0.6376 - val_tp: 5.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 4.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.5556 - val_auc: 0.6926 - val_prc: 0.6676
Epoch 34/150
29/29 [==============================] - 5s 182ms/step - loss: 0.7035 - tp: 6.0000 - fp: 13.0000 - tn: 23.0000 - fn: 16.0000 - accuracy: 0.5000 - precision: 0.3158 - recall: 0.2727 - auc: 0.5322 - prc: 0.3737 - val_loss: 0.6689 - val_tp: 5.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 4.0000 - val_accuracy: 0.5000 - val_precision: 0.3846 - val_recall: 0.5556 - val_auc: 0.6704 - val_prc: 0.6534
Epoch 35/150
29/29 [==============================] - 6s 206ms/step - loss: 0.6712 - tp: 1.0000 - fp: 2.0000 - tn: 34.0000 - fn: 21.0000 - accuracy: 0.6034 - precision: 0.3333 - recall: 0.0455 - auc: 0.5840 - prc: 0.4860 - val_loss: 0.6611 - val_tp: 6.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 3.0000 - val_accuracy: 0.5833 - val_precision: 0.4615 - val_recall: 0.6667 - val_auc: 0.7074 - val_prc: 0.6201
Epoch 36/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6275 - tp: 5.0000 - fp: 5.0000 - tn: 31.0000 - fn: 17.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2273 - auc: 0.6591 - prc: 0.4538 - val_loss: 0.6931 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.6963 - val_prc: 0.6599
Epoch 37/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6712 - tp: 6.0000 - fp: 5.0000 - tn: 31.0000 - fn: 16.0000 - accuracy: 0.6379 - precision: 0.5455 - recall: 0.2727 - auc: 0.5404 - prc: 0.4800 - val_loss: 0.6658 - val_tp: 7.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 2.0000 - val_accuracy: 0.5833 - val_precision: 0.4667 - val_recall: 0.7778 - val_auc: 0.7222 - val_prc: 0.6967
Epoch 38/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6676 - tp: 4.0000 - fp: 5.0000 - tn: 31.0000 - fn: 18.0000 - accuracy: 0.6034 - precision: 0.4444 - recall: 0.1818 - auc: 0.5486 - prc: 0.4141 - val_loss: 0.6029 - val_tp: 1.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 8.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.1111 - val_auc: 0.7000 - val_prc: 0.5160
Epoch 39/150
29/29 [==============================] - 5s 186ms/step - loss: 0.6224 - tp: 4.0000 - fp: 2.0000 - tn: 34.0000 - fn: 18.0000 - accuracy: 0.6552 - precision: 0.6667 - recall: 0.1818 - auc: 0.6578 - prc: 0.6070 - val_loss: 0.6108 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.6704 - val_prc: 0.4683
Epoch 40/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6676 - tp: 6.0000 - fp: 8.0000 - tn: 28.0000 - fn: 16.0000 - accuracy: 0.5862 - precision: 0.4286 - recall: 0.2727 - auc: 0.5726 - prc: 0.4630 - val_loss: 0.6539 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.7185 - val_prc: 0.6816
Epoch 41/150
29/29 [==============================] - 5s 183ms/step - loss: 0.7080 - tp: 1.0000 - fp: 3.0000 - tn: 33.0000 - fn: 21.0000 - accuracy: 0.5862 - precision: 0.2500 - recall: 0.0455 - auc: 0.4028 - prc: 0.3391 - val_loss: 0.6216 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.7481 - val_prc: 0.7127
Epoch 42/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6574 - tp: 4.0000 - fp: 5.0000 - tn: 31.0000 - fn: 18.0000 - accuracy: 0.6034 - precision: 0.4444 - recall: 0.1818 - auc: 0.6010 - prc: 0.4143 - val_loss: 0.6158 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7259 - val_prc: 0.6933
Epoch 43/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6293 - tp: 5.0000 - fp: 3.0000 - tn: 33.0000 - fn: 17.0000 - accuracy: 0.6552 - precision: 0.6250 - recall: 0.2273 - auc: 0.6692 - prc: 0.5125 - val_loss: 0.6061 - val_tp: 5.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 4.0000 - val_accuracy: 0.6667 - val_precision: 0.5556 - val_recall: 0.5556 - val_auc: 0.7111 - val_prc: 0.4929
Epoch 44/150
29/29 [==============================] - 5s 182ms/step - loss: 0.7083 - tp: 3.0000 - fp: 6.0000 - tn: 30.0000 - fn: 19.0000 - accuracy: 0.5690 - precision: 0.3333 - recall: 0.1364 - auc: 0.4476 - prc: 0.4012 - val_loss: 0.6599 - val_tp: 1.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 8.0000 - val_accuracy: 0.5833 - val_precision: 0.3333 - val_recall: 0.1111 - val_auc: 0.6444 - val_prc: 0.4695
Epoch 45/150
29/29 [==============================] - 6s 206ms/step - loss: 0.6447 - tp: 7.0000 - fp: 4.0000 - tn: 32.0000 - fn: 15.0000 - accuracy: 0.6724 - precision: 0.6364 - recall: 0.3182 - auc: 0.6111 - prc: 0.5782 - val_loss: 0.6556 - val_tp: 1.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 8.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.1111 - val_auc: 0.6889 - val_prc: 0.4995
Epoch 46/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6695 - tp: 4.0000 - fp: 4.0000 - tn: 32.0000 - fn: 18.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.1818 - auc: 0.5234 - prc: 0.4325 - val_loss: 0.6279 - val_tp: 1.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 8.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.1111 - val_auc: 0.6741 - val_prc: 0.4755
Epoch 47/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6543 - tp: 2.0000 - fp: 2.0000 - tn: 34.0000 - fn: 20.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.0909 - auc: 0.5726 - prc: 0.4613 - val_loss: 0.6232 - val_tp: 3.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 6.0000 - val_accuracy: 0.6667 - val_precision: 0.6000 - val_recall: 0.3333 - val_auc: 0.6630 - val_prc: 0.5356
Epoch 48/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6752 - tp: 2.0000 - fp: 4.0000 - tn: 32.0000 - fn: 20.0000 - accuracy: 0.5862 - precision: 0.3333 - recall: 0.0909 - auc: 0.5069 - prc: 0.3705 - val_loss: 0.6255 - val_tp: 5.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 4.0000 - val_accuracy: 0.6667 - val_precision: 0.5556 - val_recall: 0.5556 - val_auc: 0.7259 - val_prc: 0.6719
Epoch 49/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6410 - tp: 6.0000 - fp: 3.0000 - tn: 33.0000 - fn: 16.0000 - accuracy: 0.6724 - precision: 0.6667 - recall: 0.2727 - auc: 0.6477 - prc: 0.5384 - val_loss: 0.7278 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.6259 - val_prc: 0.4578
Epoch 50/150
29/29 [==============================] - 6s 205ms/step - loss: 0.6456 - tp: 5.0000 - fp: 5.0000 - tn: 31.0000 - fn: 17.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.2273 - auc: 0.6073 - prc: 0.4832 - val_loss: 0.5857 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.7074 - val_prc: 0.6049
Epoch 51/150
29/29 [==============================] - 5s 180ms/step - loss: 0.7014 - tp: 4.0000 - fp: 9.0000 - tn: 27.0000 - fn: 18.0000 - accuracy: 0.5345 - precision: 0.3077 - recall: 0.1818 - auc: 0.4905 - prc: 0.4029 - val_loss: 0.6040 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.6037 - val_prc: 0.4975
Epoch 52/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5984 - tp: 10.0000 - fp: 2.0000 - tn: 34.0000 - fn: 12.0000 - accuracy: 0.7586 - precision: 0.8333 - recall: 0.4545 - auc: 0.7367 - prc: 0.7033 - val_loss: 0.5748 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7296 - val_prc: 0.5922
Epoch 53/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6348 - tp: 8.0000 - fp: 5.0000 - tn: 31.0000 - fn: 14.0000 - accuracy: 0.6724 - precision: 0.6154 - recall: 0.3636 - auc: 0.6402 - prc: 0.5631 - val_loss: 0.5882 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7926 - val_prc: 0.7050
Epoch 54/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6085 - tp: 5.0000 - fp: 4.0000 - tn: 32.0000 - fn: 17.0000 - accuracy: 0.6379 - precision: 0.5556 - recall: 0.2273 - auc: 0.7241 - prc: 0.5583 - val_loss: 0.5641 - val_tp: 4.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 5.0000 - val_accuracy: 0.7500 - val_precision: 0.8000 - val_recall: 0.4444 - val_auc: 0.7556 - val_prc: 0.7083
Epoch 55/150
29/29 [==============================] - 6s 206ms/step - loss: 0.7480 - tp: 3.0000 - fp: 10.0000 - tn: 26.0000 - fn: 19.0000 - accuracy: 0.5000 - precision: 0.2308 - recall: 0.1364 - auc: 0.4116 - prc: 0.3103 - val_loss: 0.6614 - val_tp: 8.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 1.0000 - val_accuracy: 0.6667 - val_precision: 0.5333 - val_recall: 0.8889 - val_auc: 0.7519 - val_prc: 0.6442
Epoch 56/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6687 - tp: 2.0000 - fp: 7.0000 - tn: 29.0000 - fn: 20.0000 - accuracy: 0.5345 - precision: 0.2222 - recall: 0.0909 - auc: 0.5461 - prc: 0.3720 - val_loss: 0.6286 - val_tp: 2.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 7.0000 - val_accuracy: 0.5417 - val_precision: 0.3333 - val_recall: 0.2222 - val_auc: 0.6333 - val_prc: 0.5093
Epoch 57/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6409 - tp: 8.0000 - fp: 3.0000 - tn: 33.0000 - fn: 14.0000 - accuracy: 0.7069 - precision: 0.7273 - recall: 0.3636 - auc: 0.6439 - prc: 0.5363 - val_loss: 0.5970 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7111 - val_prc: 0.4876
Epoch 58/150
29/29 [==============================] - 5s 185ms/step - loss: 0.5910 - tp: 10.0000 - fp: 4.0000 - tn: 32.0000 - fn: 12.0000 - accuracy: 0.7241 - precision: 0.7143 - recall: 0.4545 - auc: 0.7506 - prc: 0.6676 - val_loss: 0.5880 - val_tp: 0.0000e+00 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 9.0000 - val_accuracy: 0.5833 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7222 - val_prc: 0.5002
Epoch 59/150
29/29 [==============================] - 6s 204ms/step - loss: 0.6581 - tp: 9.0000 - fp: 5.0000 - tn: 31.0000 - fn: 13.0000 - accuracy: 0.6897 - precision: 0.6429 - recall: 0.4091 - auc: 0.5808 - prc: 0.5330 - val_loss: 0.7256 - val_tp: 8.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 1.0000 - val_accuracy: 0.4167 - val_precision: 0.3810 - val_recall: 0.8889 - val_auc: 0.6407 - val_prc: 0.4802
Epoch 60/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6269 - tp: 7.0000 - fp: 7.0000 - tn: 29.0000 - fn: 15.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.3182 - auc: 0.6566 - prc: 0.5440 - val_loss: 0.5785 - val_tp: 3.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 6.0000 - val_accuracy: 0.7083 - val_precision: 0.7500 - val_recall: 0.3333 - val_auc: 0.7444 - val_prc: 0.6829
Epoch 61/150
29/29 [==============================] - 6s 207ms/step - loss: 0.5986 - tp: 7.0000 - fp: 3.0000 - tn: 33.0000 - fn: 15.0000 - accuracy: 0.6897 - precision: 0.7000 - recall: 0.3182 - auc: 0.7071 - prc: 0.6466 - val_loss: 0.5624 - val_tp: 5.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 4.0000 - val_accuracy: 0.7083 - val_precision: 0.6250 - val_recall: 0.5556 - val_auc: 0.7778 - val_prc: 0.7414
Epoch 62/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6476 - tp: 8.0000 - fp: 4.0000 - tn: 32.0000 - fn: 14.0000 - accuracy: 0.6897 - precision: 0.6667 - recall: 0.3636 - auc: 0.6080 - prc: 0.5822 - val_loss: 0.6408 - val_tp: 8.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 1.0000 - val_accuracy: 0.6667 - val_precision: 0.5333 - val_recall: 0.8889 - val_auc: 0.7519 - val_prc: 0.6329
Epoch 63/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6191 - tp: 9.0000 - fp: 4.0000 - tn: 32.0000 - fn: 13.0000 - accuracy: 0.7069 - precision: 0.6923 - recall: 0.4091 - auc: 0.6736 - prc: 0.5997 - val_loss: 0.5931 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.7519 - val_prc: 0.6941
Epoch 64/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5364 - tp: 10.0000 - fp: 3.0000 - tn: 33.0000 - fn: 12.0000 - accuracy: 0.7414 - precision: 0.7692 - recall: 0.4545 - auc: 0.8125 - prc: 0.7487 - val_loss: 0.7057 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7370 - val_prc: 0.5976
Epoch 65/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6301 - tp: 5.0000 - fp: 3.0000 - tn: 33.0000 - fn: 17.0000 - accuracy: 0.6552 - precision: 0.6250 - recall: 0.2273 - auc: 0.6376 - prc: 0.5758 - val_loss: 0.5733 - val_tp: 7.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 2.0000 - val_accuracy: 0.7500 - val_precision: 0.6364 - val_recall: 0.7778 - val_auc: 0.7963 - val_prc: 0.7514
Epoch 66/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6038 - tp: 8.0000 - fp: 7.0000 - tn: 29.0000 - fn: 14.0000 - accuracy: 0.6379 - precision: 0.5333 - recall: 0.3636 - auc: 0.7014 - prc: 0.5630 - val_loss: 0.6188 - val_tp: 9.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 1.0000 - val_auc: 0.8074 - val_prc: 0.7480
Epoch 67/150
29/29 [==============================] - 5s 185ms/step - loss: 0.5997 - tp: 7.0000 - fp: 5.0000 - tn: 31.0000 - fn: 15.0000 - accuracy: 0.6552 - precision: 0.5833 - recall: 0.3182 - auc: 0.6812 - prc: 0.5390 - val_loss: 0.5888 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7185 - val_prc: 0.6326
Epoch 68/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5919 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.7348 - prc: 0.6161 - val_loss: 0.7248 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.6630 - val_prc: 0.5743
Epoch 69/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6469 - tp: 11.0000 - fp: 11.0000 - tn: 25.0000 - fn: 11.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.5000 - auc: 0.6364 - prc: 0.5145 - val_loss: 0.8186 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.5963 - val_prc: 0.5537
Epoch 70/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6409 - tp: 5.0000 - fp: 6.0000 - tn: 30.0000 - fn: 17.0000 - accuracy: 0.6034 - precision: 0.4545 - recall: 0.2273 - auc: 0.6231 - prc: 0.4339 - val_loss: 0.7859 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.5407 - val_prc: 0.5091
Epoch 71/150
29/29 [==============================] - 6s 205ms/step - loss: 0.6128 - tp: 11.0000 - fp: 6.0000 - tn: 30.0000 - fn: 11.0000 - accuracy: 0.7069 - precision: 0.6471 - recall: 0.5000 - auc: 0.7083 - prc: 0.6678 - val_loss: 0.9675 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6259 - val_prc: 0.5440
Epoch 72/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6540 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.5694 - prc: 0.5458 - val_loss: 1.0076 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7148 - val_prc: 0.5536
Epoch 73/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6401 - tp: 9.0000 - fp: 9.0000 - tn: 27.0000 - fn: 13.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.4091 - auc: 0.6414 - prc: 0.5230 - val_loss: 0.7720 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6852 - val_prc: 0.5312
Epoch 74/150
29/29 [==============================] - 5s 181ms/step - loss: 0.6105 - tp: 6.0000 - fp: 4.0000 - tn: 32.0000 - fn: 16.0000 - accuracy: 0.6552 - precision: 0.6000 - recall: 0.2727 - auc: 0.6837 - prc: 0.5591 - val_loss: 0.6210 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7148 - val_prc: 0.5004
Epoch 75/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6179 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.6856 - prc: 0.5644 - val_loss: 0.9179 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.7000 - val_prc: 0.5459
Epoch 76/150
29/29 [==============================] - 6s 207ms/step - loss: 0.5325 - tp: 11.0000 - fp: 8.0000 - tn: 28.0000 - fn: 11.0000 - accuracy: 0.6724 - precision: 0.5789 - recall: 0.5000 - auc: 0.7942 - prc: 0.6587 - val_loss: 1.1924 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.5667 - val_prc: 0.5299
Epoch 77/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6737 - tp: 8.0000 - fp: 7.0000 - tn: 29.0000 - fn: 14.0000 - accuracy: 0.6379 - precision: 0.5333 - recall: 0.3636 - auc: 0.5972 - prc: 0.4402 - val_loss: 0.7186 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6148 - val_prc: 0.5530
Epoch 78/150
29/29 [==============================] - 6s 207ms/step - loss: 0.6254 - tp: 6.0000 - fp: 4.0000 - tn: 32.0000 - fn: 16.0000 - accuracy: 0.6552 - precision: 0.6000 - recall: 0.2727 - auc: 0.6610 - prc: 0.5580 - val_loss: 0.7345 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.6259 - val_prc: 0.5359
Epoch 79/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6034 - tp: 6.0000 - fp: 5.0000 - tn: 31.0000 - fn: 16.0000 - accuracy: 0.6379 - precision: 0.5455 - recall: 0.2727 - auc: 0.7083 - prc: 0.6006 - val_loss: 0.6372 - val_tp: 7.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 2.0000 - val_accuracy: 0.6667 - val_precision: 0.5385 - val_recall: 0.7778 - val_auc: 0.6444 - val_prc: 0.5230
Epoch 80/150
29/29 [==============================] - 5s 185ms/step - loss: 0.5715 - tp: 12.0000 - fp: 4.0000 - tn: 32.0000 - fn: 10.0000 - accuracy: 0.7586 - precision: 0.7500 - recall: 0.5455 - auc: 0.7393 - prc: 0.6489 - val_loss: 1.0162 - val_tp: 9.0000 - val_fp: 15.0000 - val_tn: 0.0000e+00 - val_fn: 0.0000e+00 - val_accuracy: 0.3750 - val_precision: 0.3750 - val_recall: 1.0000 - val_auc: 0.5407 - val_prc: 0.4858
Epoch 81/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5576 - tp: 12.0000 - fp: 8.0000 - tn: 28.0000 - fn: 10.0000 - accuracy: 0.6897 - precision: 0.6000 - recall: 0.5455 - auc: 0.7727 - prc: 0.6753 - val_loss: 0.8449 - val_tp: 8.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 1.0000 - val_accuracy: 0.4583 - val_precision: 0.4000 - val_recall: 0.8889 - val_auc: 0.5296 - val_prc: 0.4704
Epoch 82/150
29/29 [==============================] - 5s 186ms/step - loss: 0.6260 - tp: 7.0000 - fp: 9.0000 - tn: 27.0000 - fn: 15.0000 - accuracy: 0.5862 - precision: 0.4375 - recall: 0.3182 - auc: 0.6705 - prc: 0.5344 - val_loss: 0.7249 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7333 - val_prc: 0.6488
Epoch 83/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6625 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.5934 - prc: 0.5237 - val_loss: 0.6239 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6815 - val_prc: 0.4929
Epoch 84/150
29/29 [==============================] - 6s 207ms/step - loss: 0.6588 - tp: 7.0000 - fp: 8.0000 - tn: 28.0000 - fn: 15.0000 - accuracy: 0.6034 - precision: 0.4667 - recall: 0.3182 - auc: 0.6136 - prc: 0.4304 - val_loss: 0.5812 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.6889 - val_prc: 0.5560
Epoch 85/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5769 - tp: 7.0000 - fp: 4.0000 - tn: 32.0000 - fn: 15.0000 - accuracy: 0.6724 - precision: 0.6364 - recall: 0.3182 - auc: 0.7923 - prc: 0.6225 - val_loss: 0.6539 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7815 - val_prc: 0.6941
Epoch 86/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6371 - tp: 10.0000 - fp: 8.0000 - tn: 28.0000 - fn: 12.0000 - accuracy: 0.6552 - precision: 0.5556 - recall: 0.4545 - auc: 0.6553 - prc: 0.4990 - val_loss: 0.5598 - val_tp: 5.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 4.0000 - val_accuracy: 0.5833 - val_precision: 0.4545 - val_recall: 0.5556 - val_auc: 0.7111 - val_prc: 0.6067
Epoch 87/150
29/29 [==============================] - 5s 182ms/step - loss: 0.6124 - tp: 11.0000 - fp: 8.0000 - tn: 28.0000 - fn: 11.0000 - accuracy: 0.6724 - precision: 0.5789 - recall: 0.5000 - auc: 0.7071 - prc: 0.5848 - val_loss: 0.7889 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.6926 - val_prc: 0.5178
Epoch 88/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5571 - tp: 13.0000 - fp: 7.0000 - tn: 29.0000 - fn: 9.0000 - accuracy: 0.7241 - precision: 0.6500 - recall: 0.5909 - auc: 0.7588 - prc: 0.6341 - val_loss: 0.9594 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.6667 - val_prc: 0.5001
Epoch 89/150
29/29 [==============================] - 6s 206ms/step - loss: 0.5916 - tp: 11.0000 - fp: 10.0000 - tn: 26.0000 - fn: 11.0000 - accuracy: 0.6379 - precision: 0.5238 - recall: 0.5000 - auc: 0.7083 - prc: 0.6126 - val_loss: 0.6811 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7481 - val_prc: 0.7207
Epoch 90/150
29/29 [==============================] - 5s 184ms/step - loss: 0.5792 - tp: 13.0000 - fp: 7.0000 - tn: 29.0000 - fn: 9.0000 - accuracy: 0.7241 - precision: 0.6500 - recall: 0.5909 - auc: 0.7468 - prc: 0.6888 - val_loss: 0.5624 - val_tp: 2.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 7.0000 - val_accuracy: 0.7083 - val_precision: 1.0000 - val_recall: 0.2222 - val_auc: 0.7407 - val_prc: 0.6354
Epoch 91/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6174 - tp: 8.0000 - fp: 7.0000 - tn: 29.0000 - fn: 14.0000 - accuracy: 0.6379 - precision: 0.5333 - recall: 0.3636 - auc: 0.6679 - prc: 0.5753 - val_loss: 0.6009 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7741 - val_prc: 0.6963
Epoch 92/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6138 - tp: 8.0000 - fp: 7.0000 - tn: 29.0000 - fn: 14.0000 - accuracy: 0.6379 - precision: 0.5333 - recall: 0.3636 - auc: 0.6774 - prc: 0.5170 - val_loss: 0.5624 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.7148 - val_prc: 0.6135
Epoch 93/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6290 - tp: 13.0000 - fp: 9.0000 - tn: 27.0000 - fn: 9.0000 - accuracy: 0.6897 - precision: 0.5909 - recall: 0.5909 - auc: 0.6806 - prc: 0.5072 - val_loss: 0.5822 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.7074 - val_prc: 0.5435
Epoch 94/150
29/29 [==============================] - 6s 206ms/step - loss: 0.6012 - tp: 10.0000 - fp: 5.0000 - tn: 31.0000 - fn: 12.0000 - accuracy: 0.7069 - precision: 0.6667 - recall: 0.4545 - auc: 0.7115 - prc: 0.5411 - val_loss: 0.5738 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.7296 - val_prc: 0.6240
Epoch 95/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6244 - tp: 8.0000 - fp: 9.0000 - tn: 27.0000 - fn: 14.0000 - accuracy: 0.6034 - precision: 0.4706 - recall: 0.3636 - auc: 0.6742 - prc: 0.5485 - val_loss: 0.5757 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.7111 - val_prc: 0.5901
Epoch 96/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6106 - tp: 6.0000 - fp: 3.0000 - tn: 33.0000 - fn: 16.0000 - accuracy: 0.6724 - precision: 0.6667 - recall: 0.2727 - auc: 0.7033 - prc: 0.6131 - val_loss: 0.5921 - val_tp: 2.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 7.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.2222 - val_auc: 0.6519 - val_prc: 0.5283
Epoch 97/150
29/29 [==============================] - 5s 187ms/step - loss: 0.6145 - tp: 9.0000 - fp: 7.0000 - tn: 29.0000 - fn: 13.0000 - accuracy: 0.6552 - precision: 0.5625 - recall: 0.4091 - auc: 0.6806 - prc: 0.5688 - val_loss: 0.6388 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.5630 - val_prc: 0.4780
Epoch 98/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6289 - tp: 5.0000 - fp: 8.0000 - tn: 28.0000 - fn: 17.0000 - accuracy: 0.5690 - precision: 0.3846 - recall: 0.2273 - auc: 0.6244 - prc: 0.4785 - val_loss: 0.7110 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.6556 - val_prc: 0.6244
Epoch 99/150
29/29 [==============================] - 6s 207ms/step - loss: 0.5653 - tp: 9.0000 - fp: 2.0000 - tn: 34.0000 - fn: 13.0000 - accuracy: 0.7414 - precision: 0.8182 - recall: 0.4091 - auc: 0.7765 - prc: 0.7518 - val_loss: 0.5964 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.6704 - val_prc: 0.5604
Epoch 100/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6159 - tp: 7.0000 - fp: 6.0000 - tn: 30.0000 - fn: 15.0000 - accuracy: 0.6379 - precision: 0.5385 - recall: 0.3182 - auc: 0.6856 - prc: 0.4980 - val_loss: 0.5476 - val_tp: 3.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 6.0000 - val_accuracy: 0.6667 - val_precision: 0.6000 - val_recall: 0.3333 - val_auc: 0.7778 - val_prc: 0.7039
Epoch 101/150
29/29 [==============================] - 5s 185ms/step - loss: 0.5697 - tp: 9.0000 - fp: 4.0000 - tn: 32.0000 - fn: 13.0000 - accuracy: 0.7069 - precision: 0.6923 - recall: 0.4091 - auc: 0.7494 - prc: 0.6223 - val_loss: 0.5477 - val_tp: 1.0000 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 8.0000 - val_accuracy: 0.6667 - val_precision: 1.0000 - val_recall: 0.1111 - val_auc: 0.7926 - val_prc: 0.6801
Epoch 102/150
29/29 [==============================] - 5s 185ms/step - loss: 0.6199 - tp: 7.0000 - fp: 7.0000 - tn: 29.0000 - fn: 15.0000 - accuracy: 0.6207 - precision: 0.5000 - recall: 0.3182 - auc: 0.6660 - prc: 0.4526 - val_loss: 0.6044 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.6667 - val_prc: 0.5210
Epoch 103/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5188 - tp: 13.0000 - fp: 1.0000 - tn: 35.0000 - fn: 9.0000 - accuracy: 0.8276 - precision: 0.9286 - recall: 0.5909 - auc: 0.8365 - prc: 0.8287 - val_loss: 0.5609 - val_tp: 7.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 2.0000 - val_accuracy: 0.6667 - val_precision: 0.5385 - val_recall: 0.7778 - val_auc: 0.7481 - val_prc: 0.5854
Epoch 104/150
29/29 [==============================] - 6s 207ms/step - loss: 0.5498 - tp: 10.0000 - fp: 6.0000 - tn: 30.0000 - fn: 12.0000 - accuracy: 0.6897 - precision: 0.6250 - recall: 0.4545 - auc: 0.7803 - prc: 0.6850 - val_loss: 0.5660 - val_tp: 7.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 2.0000 - val_accuracy: 0.6667 - val_precision: 0.5385 - val_recall: 0.7778 - val_auc: 0.7370 - val_prc: 0.5807
Epoch 105/150
29/29 [==============================] - 5s 183ms/step - loss: 0.6338 - tp: 8.0000 - fp: 7.0000 - tn: 29.0000 - fn: 14.0000 - accuracy: 0.6379 - precision: 0.5333 - recall: 0.3636 - auc: 0.6313 - prc: 0.5414 - val_loss: 0.6451 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.6778 - val_prc: 0.5501
Epoch 106/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5249 - tp: 12.0000 - fp: 6.0000 - tn: 30.0000 - fn: 10.0000 - accuracy: 0.7241 - precision: 0.6667 - recall: 0.5455 - auc: 0.8138 - prc: 0.7819 - val_loss: 0.5430 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.6852 - val_prc: 0.5312
Epoch 107/150
29/29 [==============================] - 5s 186ms/step - loss: 0.5815 - tp: 15.0000 - fp: 10.0000 - tn: 26.0000 - fn: 7.0000 - accuracy: 0.7069 - precision: 0.6000 - recall: 0.6818 - auc: 0.7216 - prc: 0.5448 - val_loss: 0.8003 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.6222 - val_prc: 0.5369
Epoch 108/150
29/29 [==============================] - 5s 184ms/step - loss: 0.5578 - tp: 12.0000 - fp: 6.0000 - tn: 30.0000 - fn: 10.0000 - accuracy: 0.7241 - precision: 0.6667 - recall: 0.5455 - auc: 0.7620 - prc: 0.6217 - val_loss: 0.8668 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7333 - val_prc: 0.5797
Epoch 109/150
29/29 [==============================] - 6s 208ms/step - loss: 0.5450 - tp: 14.0000 - fp: 6.0000 - tn: 30.0000 - fn: 8.0000 - accuracy: 0.7586 - precision: 0.7000 - recall: 0.6364 - auc: 0.7847 - prc: 0.7347 - val_loss: 0.5321 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7630 - val_prc: 0.5972
Epoch 110/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5715 - tp: 14.0000 - fp: 7.0000 - tn: 29.0000 - fn: 8.0000 - accuracy: 0.7414 - precision: 0.6667 - recall: 0.6364 - auc: 0.7582 - prc: 0.6544 - val_loss: 0.5747 - val_tp: 2.0000 - val_fp: 1.0000 - val_tn: 14.0000 - val_fn: 7.0000 - val_accuracy: 0.6667 - val_precision: 0.6667 - val_recall: 0.2222 - val_auc: 0.7148 - val_prc: 0.5994
Epoch 111/150
29/29 [==============================] - 5s 186ms/step - loss: 0.5356 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8087 - prc: 0.7395 - val_loss: 0.5713 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7037 - val_prc: 0.6061
Epoch 112/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5344 - tp: 11.0000 - fp: 4.0000 - tn: 32.0000 - fn: 11.0000 - accuracy: 0.7414 - precision: 0.7333 - recall: 0.5000 - auc: 0.7923 - prc: 0.7589 - val_loss: 0.5548 - val_tp: 3.0000 - val_fp: 2.0000 - val_tn: 13.0000 - val_fn: 6.0000 - val_accuracy: 0.6667 - val_precision: 0.6000 - val_recall: 0.3333 - val_auc: 0.7148 - val_prc: 0.5722
Epoch 113/150
29/29 [==============================] - 5s 186ms/step - loss: 0.4920 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.8586 - prc: 0.8224 - val_loss: 0.5397 - val_tp: 3.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 6.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.3333 - val_auc: 0.7370 - val_prc: 0.5998
Epoch 114/150
29/29 [==============================] - 5s 184ms/step - loss: 0.6154 - tp: 8.0000 - fp: 5.0000 - tn: 31.0000 - fn: 14.0000 - accuracy: 0.6724 - precision: 0.6154 - recall: 0.3636 - auc: 0.6888 - prc: 0.5479 - val_loss: 0.9068 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.6407 - val_prc: 0.5192
Epoch 115/150
29/29 [==============================] - 6s 207ms/step - loss: 0.5012 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8750 - prc: 0.8653 - val_loss: 0.7173 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.6741 - val_prc: 0.5405
Epoch 116/150
29/29 [==============================] - 6s 207ms/step - loss: 0.5362 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.7746 - prc: 0.7763 - val_loss: 0.6689 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.6889 - val_prc: 0.5579
Epoch 117/150
29/29 [==============================] - 6s 206ms/step - loss: 0.5471 - tp: 14.0000 - fp: 7.0000 - tn: 29.0000 - fn: 8.0000 - accuracy: 0.7414 - precision: 0.6667 - recall: 0.6364 - auc: 0.7929 - prc: 0.6062 - val_loss: 0.9950 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6704 - val_prc: 0.5921
Epoch 118/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5357 - tp: 13.0000 - fp: 8.0000 - tn: 28.0000 - fn: 9.0000 - accuracy: 0.7069 - precision: 0.6190 - recall: 0.5909 - auc: 0.8087 - prc: 0.7147 - val_loss: 0.6493 - val_tp: 9.0000 - val_fp: 8.0000 - val_tn: 7.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.6667 - val_precision: 0.5294 - val_recall: 1.0000 - val_auc: 0.6963 - val_prc: 0.5473
Epoch 119/150
29/29 [==============================] - 5s 185ms/step - loss: 0.4701 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.8725 - prc: 0.8120 - val_loss: 0.5653 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.7407 - val_prc: 0.6079
Epoch 120/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5085 - tp: 15.0000 - fp: 9.0000 - tn: 27.0000 - fn: 7.0000 - accuracy: 0.7241 - precision: 0.6250 - recall: 0.6818 - auc: 0.8277 - prc: 0.8029 - val_loss: 0.7471 - val_tp: 0.0000e+00 - val_fp: 0.0000e+00 - val_tn: 15.0000 - val_fn: 9.0000 - val_accuracy: 0.6250 - val_precision: 0.0000e+00 - val_recall: 0.0000e+00 - val_auc: 0.7259 - val_prc: 0.6723
Epoch 121/150
29/29 [==============================] - 5s 185ms/step - loss: 0.4898 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.8371 - prc: 0.7237 - val_loss: 0.6696 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7333 - val_prc: 0.6027
Epoch 122/150
29/29 [==============================] - 5s 184ms/step - loss: 0.5793 - tp: 12.0000 - fp: 9.0000 - tn: 27.0000 - fn: 10.0000 - accuracy: 0.6724 - precision: 0.5714 - recall: 0.5455 - auc: 0.7330 - prc: 0.5865 - val_loss: 0.5316 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.7519 - val_prc: 0.6179
Epoch 123/150
29/29 [==============================] - 6s 208ms/step - loss: 0.5606 - tp: 11.0000 - fp: 5.0000 - tn: 31.0000 - fn: 11.0000 - accuracy: 0.7241 - precision: 0.6875 - recall: 0.5000 - auc: 0.7481 - prc: 0.6783 - val_loss: 0.5416 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.7667 - val_prc: 0.6311
Epoch 124/150
29/29 [==============================] - 5s 182ms/step - loss: 0.5782 - tp: 11.0000 - fp: 8.0000 - tn: 28.0000 - fn: 11.0000 - accuracy: 0.6724 - precision: 0.5789 - recall: 0.5000 - auc: 0.7424 - prc: 0.6540 - val_loss: 0.5523 - val_tp: 4.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 5.0000 - val_accuracy: 0.5833 - val_precision: 0.4444 - val_recall: 0.4444 - val_auc: 0.6963 - val_prc: 0.5483
Epoch 125/150
29/29 [==============================] - 5s 187ms/step - loss: 0.5540 - tp: 15.0000 - fp: 5.0000 - tn: 31.0000 - fn: 7.0000 - accuracy: 0.7931 - precision: 0.7500 - recall: 0.6818 - auc: 0.7664 - prc: 0.6315 - val_loss: 0.6888 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7185 - val_prc: 0.6165
Epoch 126/150
29/29 [==============================] - 5s 186ms/step - loss: 0.4999 - tp: 16.0000 - fp: 5.0000 - tn: 31.0000 - fn: 6.0000 - accuracy: 0.8103 - precision: 0.7619 - recall: 0.7273 - auc: 0.8359 - prc: 0.8347 - val_loss: 0.6917 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7370 - val_prc: 0.6028
Epoch 127/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5091 - tp: 14.0000 - fp: 8.0000 - tn: 28.0000 - fn: 8.0000 - accuracy: 0.7241 - precision: 0.6364 - recall: 0.6364 - auc: 0.8182 - prc: 0.7421 - val_loss: 0.5726 - val_tp: 7.0000 - val_fp: 7.0000 - val_tn: 8.0000 - val_fn: 2.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.7778 - val_auc: 0.7630 - val_prc: 0.6269
Epoch 128/150
29/29 [==============================] - 5s 186ms/step - loss: 0.5261 - tp: 12.0000 - fp: 8.0000 - tn: 28.0000 - fn: 10.0000 - accuracy: 0.6897 - precision: 0.6000 - recall: 0.5455 - auc: 0.8011 - prc: 0.6893 - val_loss: 0.5381 - val_tp: 4.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 5.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.4444 - val_auc: 0.7407 - val_prc: 0.5803
Epoch 129/150
29/29 [==============================] - 5s 184ms/step - loss: 0.5419 - tp: 10.0000 - fp: 6.0000 - tn: 30.0000 - fn: 12.0000 - accuracy: 0.6897 - precision: 0.6250 - recall: 0.4545 - auc: 0.7866 - prc: 0.7089 - val_loss: 0.6339 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.7148 - val_prc: 0.5883
Epoch 130/150
29/29 [==============================] - 5s 189ms/step - loss: 0.5201 - tp: 14.0000 - fp: 6.0000 - tn: 30.0000 - fn: 8.0000 - accuracy: 0.7586 - precision: 0.7000 - recall: 0.6364 - auc: 0.8150 - prc: 0.7406 - val_loss: 0.7827 - val_tp: 8.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 1.0000 - val_accuracy: 0.5417 - val_precision: 0.4444 - val_recall: 0.8889 - val_auc: 0.6963 - val_prc: 0.5670
Epoch 131/150
29/29 [==============================] - 5s 185ms/step - loss: 0.5769 - tp: 10.0000 - fp: 8.0000 - tn: 28.0000 - fn: 12.0000 - accuracy: 0.6552 - precision: 0.5556 - recall: 0.4545 - auc: 0.7393 - prc: 0.5730 - val_loss: 0.7029 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7556 - val_prc: 0.5191
Epoch 132/150
29/29 [==============================] - 6s 211ms/step - loss: 0.4640 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.8592 - prc: 0.7727 - val_loss: 0.6821 - val_tp: 9.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5833 - val_precision: 0.4737 - val_recall: 1.0000 - val_auc: 0.7296 - val_prc: 0.5268
Epoch 133/150
29/29 [==============================] - 5s 185ms/step - loss: 0.4724 - tp: 15.0000 - fp: 4.0000 - tn: 32.0000 - fn: 7.0000 - accuracy: 0.8103 - precision: 0.7895 - recall: 0.6818 - auc: 0.8567 - prc: 0.8352 - val_loss: 0.9136 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6778 - val_prc: 0.5550
Epoch 134/150
29/29 [==============================] - 6s 206ms/step - loss: 0.4977 - tp: 12.0000 - fp: 4.0000 - tn: 32.0000 - fn: 10.0000 - accuracy: 0.7586 - precision: 0.7500 - recall: 0.5455 - auc: 0.8232 - prc: 0.7806 - val_loss: 0.7380 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.6444 - val_prc: 0.4939
Epoch 135/150
29/29 [==============================] - 5s 183ms/step - loss: 0.4914 - tp: 13.0000 - fp: 5.0000 - tn: 31.0000 - fn: 9.0000 - accuracy: 0.7586 - precision: 0.7222 - recall: 0.5909 - auc: 0.8295 - prc: 0.8147 - val_loss: 0.7016 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.6741 - val_prc: 0.4743
Epoch 136/150
29/29 [==============================] - 5s 181ms/step - loss: 0.4006 - tp: 18.0000 - fp: 6.0000 - tn: 30.0000 - fn: 4.0000 - accuracy: 0.8276 - precision: 0.7500 - recall: 0.8182 - auc: 0.9160 - prc: 0.8728 - val_loss: 0.8513 - val_tp: 7.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 2.0000 - val_accuracy: 0.5417 - val_precision: 0.4375 - val_recall: 0.7778 - val_auc: 0.6704 - val_prc: 0.4851
Epoch 137/150
29/29 [==============================] - 5s 185ms/step - loss: 0.4486 - tp: 14.0000 - fp: 5.0000 - tn: 31.0000 - fn: 8.0000 - accuracy: 0.7759 - precision: 0.7368 - recall: 0.6364 - auc: 0.8586 - prc: 0.8096 - val_loss: 0.9344 - val_tp: 6.0000 - val_fp: 10.0000 - val_tn: 5.0000 - val_fn: 3.0000 - val_accuracy: 0.4583 - val_precision: 0.3750 - val_recall: 0.6667 - val_auc: 0.5889 - val_prc: 0.4850
Epoch 138/150
29/29 [==============================] - 5s 183ms/step - loss: 0.5557 - tp: 13.0000 - fp: 7.0000 - tn: 29.0000 - fn: 9.0000 - accuracy: 0.7241 - precision: 0.6500 - recall: 0.5909 - auc: 0.7740 - prc: 0.7189 - val_loss: 0.7317 - val_tp: 6.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 3.0000 - val_accuracy: 0.5000 - val_precision: 0.4000 - val_recall: 0.6667 - val_auc: 0.6185 - val_prc: 0.5282
Epoch 139/150
29/29 [==============================] - 6s 208ms/step - loss: 0.5169 - tp: 12.0000 - fp: 5.0000 - tn: 31.0000 - fn: 10.0000 - accuracy: 0.7414 - precision: 0.7059 - recall: 0.5455 - auc: 0.7955 - prc: 0.7069 - val_loss: 0.5705 - val_tp: 3.0000 - val_fp: 4.0000 - val_tn: 11.0000 - val_fn: 6.0000 - val_accuracy: 0.5833 - val_precision: 0.4286 - val_recall: 0.3333 - val_auc: 0.7296 - val_prc: 0.6653
Epoch 140/150
29/29 [==============================] - 5s 184ms/step - loss: 0.4208 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.8902 - prc: 0.8377 - val_loss: 0.7661 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7111 - val_prc: 0.6723
Epoch 141/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4170 - tp: 17.0000 - fp: 6.0000 - tn: 30.0000 - fn: 5.0000 - accuracy: 0.8103 - precision: 0.7391 - recall: 0.7727 - auc: 0.8996 - prc: 0.8173 - val_loss: 1.0633 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.6667 - val_prc: 0.4958
Epoch 142/150
29/29 [==============================] - 5s 186ms/step - loss: 0.4598 - tp: 13.0000 - fp: 4.0000 - tn: 32.0000 - fn: 9.0000 - accuracy: 0.7759 - precision: 0.7647 - recall: 0.5909 - auc: 0.8504 - prc: 0.8274 - val_loss: 0.9489 - val_tp: 9.0000 - val_fp: 12.0000 - val_tn: 3.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5000 - val_precision: 0.4286 - val_recall: 1.0000 - val_auc: 0.6185 - val_prc: 0.4544
Epoch 143/150
29/29 [==============================] - 5s 183ms/step - loss: 0.4329 - tp: 16.0000 - fp: 6.0000 - tn: 30.0000 - fn: 6.0000 - accuracy: 0.7931 - precision: 0.7273 - recall: 0.7273 - auc: 0.8782 - prc: 0.8446 - val_loss: 0.9654 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.6778 - val_prc: 0.5528
Epoch 144/150
29/29 [==============================] - 6s 200ms/step - loss: 0.4520 - tp: 16.0000 - fp: 4.0000 - tn: 32.0000 - fn: 6.0000 - accuracy: 0.8276 - precision: 0.8000 - recall: 0.7273 - auc: 0.8611 - prc: 0.7639 - val_loss: 1.3029 - val_tp: 9.0000 - val_fp: 13.0000 - val_tn: 2.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.4583 - val_precision: 0.4091 - val_recall: 1.0000 - val_auc: 0.6185 - val_prc: 0.5865
Epoch 145/150
29/29 [==============================] - 6s 198ms/step - loss: 0.4697 - tp: 18.0000 - fp: 9.0000 - tn: 27.0000 - fn: 4.0000 - accuracy: 0.7759 - precision: 0.6667 - recall: 0.8182 - auc: 0.8409 - prc: 0.7420 - val_loss: 0.8416 - val_tp: 8.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 1.0000 - val_accuracy: 0.5000 - val_precision: 0.4211 - val_recall: 0.8889 - val_auc: 0.6000 - val_prc: 0.5343
Epoch 146/150
29/29 [==============================] - 6s 216ms/step - loss: 0.4762 - tp: 13.0000 - fp: 4.0000 - tn: 32.0000 - fn: 9.0000 - accuracy: 0.7759 - precision: 0.7647 - recall: 0.5909 - auc: 0.8396 - prc: 0.7806 - val_loss: 0.7761 - val_tp: 8.0000 - val_fp: 9.0000 - val_tn: 6.0000 - val_fn: 1.0000 - val_accuracy: 0.5833 - val_precision: 0.4706 - val_recall: 0.8889 - val_auc: 0.6889 - val_prc: 0.5789
Epoch 147/150
29/29 [==============================] - 5s 184ms/step - loss: 0.3946 - tp: 16.0000 - fp: 3.0000 - tn: 33.0000 - fn: 6.0000 - accuracy: 0.8448 - precision: 0.8421 - recall: 0.7273 - auc: 0.9091 - prc: 0.8527 - val_loss: 0.5931 - val_tp: 6.0000 - val_fp: 5.0000 - val_tn: 10.0000 - val_fn: 3.0000 - val_accuracy: 0.6667 - val_precision: 0.5455 - val_recall: 0.6667 - val_auc: 0.7111 - val_prc: 0.5656
Epoch 148/150
29/29 [==============================] - 5s 182ms/step - loss: 0.4193 - tp: 18.0000 - fp: 3.0000 - tn: 33.0000 - fn: 4.0000 - accuracy: 0.8793 - precision: 0.8571 - recall: 0.8182 - auc: 0.9003 - prc: 0.9016 - val_loss: 0.6307 - val_tp: 4.0000 - val_fp: 3.0000 - val_tn: 12.0000 - val_fn: 5.0000 - val_accuracy: 0.6667 - val_precision: 0.5714 - val_recall: 0.4444 - val_auc: 0.6815 - val_prc: 0.6220
Epoch 149/150
29/29 [==============================] - 5s 181ms/step - loss: 0.5422 - tp: 14.0000 - fp: 9.0000 - tn: 27.0000 - fn: 8.0000 - accuracy: 0.7069 - precision: 0.6087 - recall: 0.6364 - auc: 0.7734 - prc: 0.7439 - val_loss: 0.6075 - val_tp: 6.0000 - val_fp: 6.0000 - val_tn: 9.0000 - val_fn: 3.0000 - val_accuracy: 0.6250 - val_precision: 0.5000 - val_recall: 0.6667 - val_auc: 0.6778 - val_prc: 0.4324
Epoch 150/150
29/29 [==============================] - 5s 184ms/step - loss: 0.4843 - tp: 13.0000 - fp: 4.0000 - tn: 32.0000 - fn: 9.0000 - accuracy: 0.7759 - precision: 0.7647 - recall: 0.5909 - auc: 0.8308 - prc: 0.7820 - val_loss: 0.7802 - val_tp: 9.0000 - val_fp: 11.0000 - val_tn: 4.0000 - val_fn: 0.0000e+00 - val_accuracy: 0.5417 - val_precision: 0.4500 - val_recall: 1.0000 - val_auc: 0.7185 - val_prc: 0.6671
Performance evaluation
Once the training is completed, the model performance can be plotted. Since the validation set is unbalanced, as already specified, the ROC AUC is used to provide a representation of the model’s performance.
fig, ax = plt.subplots(1, 2, figsize=(20, 5))
ax = ax.ravel()
for i, metric in enumerate(["auc", "val_auc"]):
for label, history in performance.items():
ax[i].plot(history.history[metric])
ax[i].set_title("Model {}".format(metric))
ax[i].set_xlabel("epochs")
ax[i].set_ylabel(metric)
ax[i].set_ylim([0.2, 1])
ax[i].legend(performance.keys())
fig, ax = plt.subplots(1, 2, figsize=(20, 5))
ax = ax.ravel()
for i, metric in enumerate(["loss", "val_loss"]):
for label, history in performance.items():
ax[i].plot(history.history[metric])
ax[i].set_title("Model {}".format(metric))
ax[i].set_xlabel("epochs")
ax[i].set_ylabel(metric)
ax[i].legend(performance.keys())
Conclusions
- Without augmentation the model overfits after few epochs and the validation AUC only reaches a maximum of 72.9%.
- Basic augmentation does not change the model behavior, rather it seems to make it even worse. It could be expected since contrast and brightness alone are not so powerful augmentation techniques.
- The intermediate case appears promising since it allows to achieve a validation AUC of 85% with a false negatives rate of 0%. This is an important aspect since it is much better a false positive than a false negative in case of brain stroke diagnosis.
- Advanced augmentation is probably distorting too much the CT scans with a negative impact on the model performance with respect to the intermediate case.
Please note the present notebook is also available on my GitHub. Feel free to run it on your own to try to improve the model performance.
References
Giovanni Pecoraro
Senior Security Engineer
My research interests include space systems, cyber security, signal processing and artificial intelligence.