combine_inceptions.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"combine_inceptions","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"emMLaddWnGFl","colab_type":"code","outputId":"0c8515d2-32a5-4691-819e-cc5d2fe00035","executionInfo":{"status":"ok","timestamp":1591115697706,"user_tz":-120,"elapsed":2632,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":52}},"source":["from google.colab import drive\n","drive.mount('/content/gdrive', force_remount=True)\n","%cd \"/content/gdrive/My Drive/Colab Notebooks/MRNet/\""],"execution_count":1,"outputs":[{"output_type":"stream","text":["Mounted at /content/gdrive\n","/content/gdrive/My Drive/Colab Notebooks/MRNet\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"qTBTNaPZn3bM","colab_type":"code","outputId":"7c7cb493-7f61-44cf-f42f-76cbb8c87a1f","executionInfo":{"status":"ok","timestamp":1591115699419,"user_tz":-120,"elapsed":3270,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["import os\n","import numpy as np\n","import glob\n","import csv\n","import keras\n","import scipy\n","from partition import partition\n","from LR_inception_generator  import MRNet_data_generator\n","from keras.layers import Conv2D,Input, MaxPool2D, AveragePooling2D, Dropout, Dense, Flatten\n","from keras.preprocessing.image import ImageDataGenerator\n","from PIL import Image\n","from matplotlib.pyplot import imshow\n","import random\n","from numpy.random import seed\n","from sklearn.utils import class_weight\n","\n","from inception_model_generator import MRNet_inc_model\n","from LR_model import LR_model\n","import tensorflow as tf\n"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Using TensorFlow backend.\n"],"name":"stderr"}]},{"cell_type":"code","metadata":{"id":"HeqsSNkii_iW","colab_type":"code","colab":{}},"source":["\n","def Savepredictions(label_type):\n","  data_path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/dataset/MRNet-v1.0\"\n","  p, l = partition(data_path)\n","  \n","  exam_view = 'axial'\n","\n","  train_data_gen = MRNet_data_generator(data_path, p, l, batch_size=1,data_type='train',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","  test_data_gen =  MRNet_data_generator(data_path, p, l, batch_size=1,data_type='test',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","  valid_data_gen =  MRNet_data_generator(data_path, p, l, batch_size=1,data_type='valid',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n"," \n","  model_axial, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_axial.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['train'][exam_view])\n","  output_train_1 = model_axial.predict_generator(train_data_gen, data_length, verbose=1)\n","  \n","  model_axial, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_axial.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['test'][exam_view])\n","  output_test_1 = model_axial.predict_generator(test_data_gen, data_length, verbose=1)\n","  \n","  model_axial, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_axial.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['valid'][exam_view])\n","  output_valid_1 = model_axial.predict_generator(valid_data_gen, data_length, verbose=1)\n"," \n","\n","  exam_view = 'coronal'\n","\n","  train_data_gen = MRNet_data_generator(data_path, p, l, batch_size=1,data_type='train',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","  test_data_gen =  MRNet_data_generator(data_path, p, l, batch_size=1,data_type='test',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","  valid_data_gen =  MRNet_data_generator(data_path, p, l, batch_size=1,data_type='valid',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n"," \n","  model_coronal, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_coronal.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['train'][exam_view])\n","  output_train_2 = model_coronal.predict_generator(train_data_gen, data_length, verbose=1)\n"," \n","  model_coronal, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_coronal.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")  \n","  data_length = len(p['test'][exam_view])\n","  output_test_2 = model_coronal.predict_generator(test_data_gen, data_length, verbose=1)\n","  \n","  model_coronal, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_coronal.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['valid'][exam_view])\n","  output_valid_2 = model_coronal.predict_generator(valid_data_gen, data_length, verbose=1)\n","  \n","  \n","  \n","  exam_view = 'sagittal'\n","  \n","  train_data_gen = MRNet_data_generator(data_path, p, l, batch_size=1,data_type='train',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","  test_data_gen =  MRNet_data_generator(data_path, p, l, batch_size=1,data_type='test',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","  valid_data_gen =  MRNet_data_generator(data_path, p, l, batch_size=1,data_type='valid',label_type=label_type, exam_type=exam_view, scale_to=(299,299))\n","\n","  model_sagittal, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_sagittal.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['train'][exam_view])\n","  output_train_3 = model_sagittal.predict_generator(train_data_gen, data_length, verbose=1)\n","  \n","  model_sagittal, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_sagittal.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['test'][exam_view])\n","  output_test_3 = model_sagittal.predict_generator(test_data_gen, data_length, verbose=1)\n","  \n","  model_sagittal, cbs = MRNet_inc_model(1,0.00001,combination=[label_type, exam_view])\n","  model_sagittal.load_weights(\"/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception/\"+label_type+\"/\"+exam_view+\"/best.hdf5\")\n","  data_length = len(p['valid'][exam_view])\n","  output_valid_3 = model_sagittal.predict_generator(valid_data_gen, data_length, verbose=1)\n","  \n","  \n","  ids = list(map(int, p['train'][exam_view]))\n","  ids = sorted(ids)\n","  print(ids)\n","  narr = np.array(ids).reshape(len(ids),1)\n","  output_train = np.stack((narr,output_train_1,output_train_2,output_train_3),axis=1)\n","  output_train = np.squeeze(output_train)\n","  path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/\"+\"train-\"+label_type+\".csv\"\n","  np.savetxt(path, output_train, delimiter=\",\")\n","  \n","  ids = list(map(int, p['test'][exam_view]))\n","  ids = sorted(ids)\n","  print(ids)\n","  narr = np.array(ids).reshape(len(ids),1)\n","  output_test = np.stack((narr,output_test_1,output_test_2,output_test_3),axis=1)\n","  output_test = np.squeeze(output_test)\n","  path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/\"+\"test-\"+label_type+\".csv\"\n","  np.savetxt(path, output_test, delimiter=\",\")\n","\n","  ids = list(map(int, p['valid'][exam_view]))\n","  ids = sorted(ids)\n","  print(ids)\n","  narr = np.array(ids).reshape(len(ids),1)\n","  output_valid = np.stack((narr,output_valid_1,output_valid_2,output_valid_3),axis=1)\n","  output_valid = np.squeeze(output_valid)\n","  path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/\"+\"valid-\"+label_type+\".csv\"\n","  np.savetxt(path, output_valid, delimiter=\",\")\n","  \n","  \n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Mz4ta0UslnAZ","colab_type":"code","colab":{}},"source":["Savepredictions(\"abnormal\");\n","Savepredictions(\"ACL\");\n","Savepredictions(\"meniscus\");"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"rXKl4ZBChymz","colab_type":"text"},"source":["# **Abnormal**"]},{"cell_type":"code","metadata":{"id":"nHIC38o9xJWG","colab_type":"code","outputId":"2b3aa5d7-2a55-4a57-a28a-f3a1ae0581ce","executionInfo":{"status":"ok","timestamp":1591117161613,"user_tz":-120,"elapsed":86356,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["# load train, test,  valid data \n","label_type = \"abnormal\"\n","exam_view =\"axial\"\n","data_path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/dataset/MRNet-v1.0\"\n","p, l = partition(data_path)\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/train-abnormal.csv', newline='') as csvfile:\n","      data_train = list(csv.reader(csvfile))\n","x_train = np.array(data_train,dtype='float32')\n","x_train  = x_train[:,1:4]\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/test-abnormal.csv', newline='') as csvfile:\n","      data_test = list(csv.reader(csvfile))\n","x_test = np.array(data_test,dtype='float32')\n","x_test  = x_test[:,1:4]\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/valid-abnormal.csv', newline='') as csvfile:\n","      data_valid = list(csv.reader(csvfile))\n","x_valid = np.array(data_valid,dtype='float32')\n","x_valid  = x_valid[:,1:4]\n","\n","# load labels\n","ids_train = sorted(p['train'][exam_view]);\n","ids_test = sorted(p['test'][exam_view]);\n","ids_valid = sorted(p['valid'][exam_view]);\n","\n","arr = [] \n","for e in ids_train:\n","  arr.append(l[e][label_type]);\n","\n","y_train = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","arr = [] \n","for e in ids_test:\n","  arr.append(l[e][label_type]);\n","\n","y_test = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","arr = [] \n","for e in ids_valid:\n","  arr.append(l[e][label_type]);\n","  \n","y_valid = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","# class weight for skewed classes\n","pos = 0\n","for e in p['train'][exam_view]:\n","  if l[e][label_type] == 1:\n","    pos += 1\n","total = len(p['train'][exam_view])\n","neg = total - pos\n","class_weight = {0: 1, 1: neg/pos}\n","if neg < pos:\n","  class_weight = {0: pos/neg, 1: 1}\n","\n","\n","model,cbs = LR_model(0.001,label = \"abnormal\",modelName=\"inception\");\n","model.fit(x=x_train,y=y_train, validation_data =[x_test,y_test] ,epochs=100, initial_epoch = 0,verbose=1, class_weight=class_weight,callbacks=[cbs[0]],shuffle=False, use_multiprocessing=True, workers=6)"],"execution_count":45,"outputs":[{"output_type":"stream","text":["Train on 1017 samples, validate on 113 samples\n","Epoch 1/100\n","1017/1017 [==============================] - 0s 332us/step - loss: 1.3410 - tp: 7.9062 - fp: 31.8438 - tn: 69.5312 - fn: 418.5000 - accuracy: 0.1516 - precision: 0.2296 - recall: 0.0220 - auc: 0.0419 - val_loss: 0.8139 - val_tp: 21.7500 - val_fp: 67.2500 - val_tn: 140.7500 - val_fn: 863.5000 - val_accuracy: 0.1485 - val_precision: 0.2425 - val_recall: 0.0245 - val_auc: 0.0718\n","\n","Epoch 00001: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.01.hdf5\n","Epoch 2/100\n","1017/1017 [==============================] - 0s 145us/step - loss: 1.3022 - tp: 44.7188 - fp: 111.5312 - tn: 206.8438 - fn: 1294.6875 - accuracy: 0.1525 - precision: 0.2893 - recall: 0.0335 - auc: 0.0801 - val_loss: 0.7794 - val_tp: 66.2500 - val_fp: 158.2500 - val_tn: 266.7500 - val_fn: 1732.0000 - val_accuracy: 0.1497 - val_precision: 0.2947 - val_recall: 0.0368 - val_auc: 0.0906\n","\n","Epoch 00002: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.02.hdf5\n","Epoch 3/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 1.2662 - tp: 96.0000 - fp: 210.2812 - tn: 325.0938 - fn: 2156.4062 - accuracy: 0.1514 - precision: 0.3146 - recall: 0.0426 - auc: 0.0959 - val_loss: 0.7479 - val_tp: 127.2500 - val_fp: 267.2500 - val_tn: 374.7500 - val_fn: 2584.0000 - val_accuracy: 0.1497 - val_precision: 0.3224 - val_recall: 0.0469 - val_auc: 0.1046\n","\n","Epoch 00003: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.03.hdf5\n","Epoch 4/100\n","1017/1017 [==============================] - 0s 143us/step - loss: 1.2326 - tp: 171.6875 - fp: 330.0000 - tn: 422.3750 - fn: 2993.7188 - accuracy: 0.1517 - precision: 0.3422 - recall: 0.0541 - auc: 0.1107 - val_loss: 0.7192 - val_tp: 221.2500 - val_fp: 394.2500 - val_tn: 464.7500 - val_fn: 3403.0000 - val_accuracy: 0.1530 - val_precision: 0.3594 - val_recall: 0.0610 - val_auc: 0.1205\n","\n","Epoch 00004: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.04.hdf5\n","Epoch 5/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 1.2013 - tp: 289.6250 - fp: 460.6875 - tn: 508.6875 - fn: 3788.7812 - accuracy: 0.1581 - precision: 0.3853 - recall: 0.0708 - auc: 0.1297 - val_loss: 0.6931 - val_tp: 360.7500 - val_fp: 527.7500 - val_tn: 548.2500 - val_fn: 4176.5000 - val_accuracy: 0.1619 - val_precision: 0.4060 - val_recall: 0.0795 - val_auc: 0.1431\n","\n","Epoch 00005: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.05.hdf5\n","Epoch 6/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 1.1720 - tp: 470.6562 - fp: 598.6250 - tn: 587.7500 - fn: 4520.7500 - accuracy: 0.1711 - precision: 0.4385 - recall: 0.0939 - auc: 0.1584 - val_loss: 0.6694 - val_tp: 632.0000 - val_fp: 667.7500 - val_tn: 625.2500 - val_fn: 4818.2500 - val_accuracy: 0.1864 - val_precision: 0.4862 - val_recall: 0.1159 - val_auc: 0.1784\n","\n","Epoch 00006: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.06.hdf5\n","Epoch 7/100\n","1017/1017 [==============================] - 0s 131us/step - loss: 1.1445 - tp: 895.9062 - fp: 740.7500 - tn: 662.6250 - fn: 5008.5000 - accuracy: 0.2127 - precision: 0.5443 - recall: 0.1510 - auc: 0.2017 - val_loss: 0.6478 - val_tp: 1196.2500 - val_fp: 811.2500 - val_tn: 698.7500 - val_fn: 5167.0000 - val_accuracy: 0.2407 - val_precision: 0.5959 - val_recall: 0.1880 - val_auc: 0.2281\n","\n","Epoch 00007: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.07.hdf5\n","Epoch 8/100\n","1017/1017 [==============================] - 0s 142us/step - loss: 1.1187 - tp: 1544.0312 - fp: 887.0625 - tn: 733.3125 - fn: 5273.3750 - accuracy: 0.2694 - precision: 0.6335 - recall: 0.2258 - auc: 0.2549 - val_loss: 0.6281 - val_tp: 1907.2500 - val_fp: 958.5000 - val_tn: 768.5000 - val_fn: 5369.0000 - val_accuracy: 0.2972 - val_precision: 0.6655 - val_recall: 0.2621 - val_auc: 0.2824\n","\n","Epoch 00008: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.08.hdf5\n","Epoch 9/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 1.0942 - tp: 2287.8125 - fp: 1035.4062 - tn: 801.9688 - fn: 5442.5938 - accuracy: 0.3225 - precision: 0.6877 - recall: 0.2954 - auc: 0.3083 - val_loss: 0.6102 - val_tp: 2679.5000 - val_fp: 1110.2500 - val_tn: 833.7500 - val_fn: 5509.7500 - val_accuracy: 0.3467 - val_precision: 0.7070 - val_recall: 0.3272 - val_auc: 0.3340\n","\n","Epoch 00009: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.09.hdf5\n","Epoch 10/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 1.0711 - tp: 3071.8125 - fp: 1187.9062 - tn: 866.4688 - fn: 5571.5938 - accuracy: 0.3678 - precision: 0.7207 - recall: 0.3550 - auc: 0.3575 - val_loss: 0.5938 - val_tp: 3476.7500 - val_fp: 1263.2500 - val_tn: 897.7500 - val_fn: 5625.5000 - val_accuracy: 0.3884 - val_precision: 0.7335 - val_recall: 0.3820 - val_auc: 0.3806\n","\n","Epoch 00010: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.10.hdf5\n","Epoch 11/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 1.0491 - tp: 3883.3750 - fp: 1340.0312 - tn: 931.3438 - fn: 5673.0312 - accuracy: 0.4068 - precision: 0.7432 - recall: 0.4061 - auc: 0.4017 - val_loss: 0.5789 - val_tp: 4297.2500 - val_fp: 1415.5000 - val_tn: 962.5000 - val_fn: 5718.0000 - val_accuracy: 0.4244 - val_precision: 0.7522 - val_recall: 0.4291 - val_auc: 0.4223\n","\n","Epoch 00011: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.11.hdf5\n","Epoch 12/100\n","1017/1017 [==============================] - 0s 129us/step - loss: 1.0281 - tp: 4712.8125 - fp: 1491.0312 - tn: 997.3438 - fn: 5756.5938 - accuracy: 0.4405 - precision: 0.7595 - recall: 0.4499 - auc: 0.4411 - val_loss: 0.5652 - val_tp: 5136.0000 - val_fp: 1565.7500 - val_tn: 1029.2500 - val_fn: 5792.2500 - val_accuracy: 0.4559 - val_precision: 0.7664 - val_recall: 0.4700 - val_auc: 0.4593\n","\n","Epoch 00012: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.12.hdf5\n","Epoch 13/100\n","1017/1017 [==============================] - 0s 152us/step - loss: 1.0081 - tp: 5558.7188 - fp: 1636.5625 - tn: 1068.8125 - fn: 5823.6875 - accuracy: 0.4703 - precision: 0.7724 - recall: 0.4882 - auc: 0.4762 - val_loss: 0.5526 - val_tp: 5987.0000 - val_fp: 1707.7500 - val_tn: 1104.2500 - val_fn: 5854.2500 - val_accuracy: 0.4839 - val_precision: 0.7781 - val_recall: 0.5056 - val_auc: 0.4923\n","\n","Epoch 00013: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.13.hdf5\n","Epoch 14/100\n","1017/1017 [==============================] - 0s 144us/step - loss: 0.9888 - tp: 6414.5312 - fp: 1776.0312 - tn: 1146.3438 - fn: 5880.8750 - accuracy: 0.4967 - precision: 0.7831 - recall: 0.5215 - auc: 0.5075 - val_loss: 0.5411 - val_tp: 6848.0000 - val_fp: 1843.7500 - val_tn: 1185.2500 - val_fn: 5906.2500 - val_accuracy: 0.5090 - val_precision: 0.7879 - val_recall: 0.5369 - val_auc: 0.5219\n","\n","Epoch 00014: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.14.hdf5\n","Epoch 15/100\n","1017/1017 [==============================] - 0s 143us/step - loss: 0.9704 - tp: 7278.3438 - fp: 1907.4688 - tn: 1231.9062 - fn: 5930.0625 - accuracy: 0.5205 - precision: 0.7923 - recall: 0.5509 - auc: 0.5356 - val_loss: 0.5304 - val_tp: 7715.7500 - val_fp: 1969.7500 - val_tn: 1276.2500 - val_fn: 5951.5000 - val_accuracy: 0.5317 - val_precision: 0.7966 - val_recall: 0.5645 - val_auc: 0.5486\n","\n","Epoch 00015: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.15.hdf5\n","Epoch 16/100\n","1017/1017 [==============================] - 0s 143us/step - loss: 0.9525 - tp: 8151.6250 - fp: 2028.7500 - tn: 1327.6250 - fn: 5969.7812 - accuracy: 0.5423 - precision: 0.8007 - recall: 0.5771 - auc: 0.5610 - val_loss: 0.5206 - val_tp: 8590.7500 - val_fp: 2084.7500 - val_tn: 1378.2500 - val_fn: 5989.5000 - val_accuracy: 0.5525 - val_precision: 0.8047 - val_recall: 0.5892 - val_auc: 0.5727\n","\n","Epoch 00016: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.16.hdf5\n","Epoch 17/100\n","1017/1017 [==============================] - 0s 139us/step - loss: 0.9354 - tp: 9028.5312 - fp: 2137.1250 - tn: 1436.2500 - fn: 6005.8750 - accuracy: 0.5623 - precision: 0.8086 - recall: 0.6004 - auc: 0.5841 - val_loss: 0.5115 - val_tp: 9469.7500 - val_fp: 2189.7500 - val_tn: 1490.2500 - val_fn: 6023.5000 - val_accuracy: 0.5716 - val_precision: 0.8122 - val_recall: 0.6112 - val_auc: 0.5948\n","\n","Epoch 00017: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.17.hdf5\n","Epoch 18/100\n","1017/1017 [==============================] - 0s 144us/step - loss: 0.9187 - tp: 9908.0312 - fp: 2232.7188 - tn: 1557.6562 - fn: 6039.3750 - accuracy: 0.5808 - precision: 0.8161 - recall: 0.6212 - auc: 0.6052 - val_loss: 0.5030 - val_tp: 10351.2500 - val_fp: 2279.7500 - val_tn: 1617.2500 - val_fn: 6055.0000 - val_accuracy: 0.5895 - val_precision: 0.8195 - val_recall: 0.6309 - val_auc: 0.6149\n","\n","Epoch 00018: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.18.hdf5\n","Epoch 19/100\n","1017/1017 [==============================] - 0s 144us/step - loss: 0.9026 - tp: 10791.5625 - fp: 2318.0000 - tn: 1689.3750 - fn: 6068.8438 - accuracy: 0.5980 - precision: 0.8231 - recall: 0.6400 - auc: 0.6245 - val_loss: 0.4952 - val_tp: 11236.7500 - val_fp: 2358.7500 - val_tn: 1755.2500 - val_fn: 6082.5000 - val_accuracy: 0.6062 - val_precision: 0.8265 - val_recall: 0.6488 - val_auc: 0.6334\n","\n","Epoch 00019: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.19.hdf5\n","Epoch 20/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.8870 - tp: 11679.9375 - fp: 2392.3438 - tn: 1832.0312 - fn: 6093.4688 - accuracy: 0.6142 - precision: 0.8300 - recall: 0.6571 - auc: 0.6423 - val_loss: 0.4879 - val_tp: 12125.7500 - val_fp: 2431.2500 - val_tn: 1899.7500 - val_fn: 6106.5000 - val_accuracy: 0.6216 - val_precision: 0.8330 - val_recall: 0.6651 - val_auc: 0.6505\n","\n","Epoch 00020: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.20.hdf5\n","Epoch 21/100\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.8718 - tp: 12569.3438 - fp: 2461.8438 - tn: 1979.5312 - fn: 6117.0625 - accuracy: 0.6290 - precision: 0.8362 - recall: 0.6726 - auc: 0.6587 - val_loss: 0.4810 - val_tp: 13015.7500 - val_fp: 2497.5000 - val_tn: 2050.5000 - val_fn: 6129.5000 - val_accuracy: 0.6359 - val_precision: 0.8390 - val_recall: 0.6798 - val_auc: 0.6663\n","\n","Epoch 00021: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.21.hdf5\n","Epoch 22/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.8570 - tp: 13459.0312 - fp: 2525.1250 - tn: 2133.2500 - fn: 6140.3750 - accuracy: 0.6427 - precision: 0.8420 - recall: 0.6867 - auc: 0.6739 - val_loss: 0.4747 - val_tp: 13905.7500 - val_fp: 2558.5000 - val_tn: 2206.5000 - val_fn: 6152.5000 - val_accuracy: 0.6491 - val_precision: 0.8446 - val_recall: 0.6933 - val_auc: 0.6809\n","\n","Epoch 00022: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.22.hdf5\n","Epoch 23/100\n","1017/1017 [==============================] - 0s 145us/step - loss: 0.8426 - tp: 14349.0312 - fp: 2584.2188 - tn: 2291.1562 - fn: 6163.3750 - accuracy: 0.6554 - precision: 0.8474 - recall: 0.6995 - auc: 0.6881 - val_loss: 0.4687 - val_tp: 14796.0000 - val_fp: 2614.5000 - val_tn: 2367.5000 - val_fn: 6175.2500 - val_accuracy: 0.6613 - val_precision: 0.8498 - val_recall: 0.7055 - val_auc: 0.6946\n","\n","Epoch 00023: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.23.hdf5\n","Epoch 24/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.8286 - tp: 15240.1875 - fp: 2638.4688 - tn: 2453.9062 - fn: 6185.2188 - accuracy: 0.6672 - precision: 0.8524 - recall: 0.7113 - auc: 0.7012 - val_loss: 0.4630 - val_tp: 15688.0000 - val_fp: 2667.5000 - val_tn: 2531.5000 - val_fn: 6196.2500 - val_accuracy: 0.6727 - val_precision: 0.8547 - val_recall: 0.7169 - val_auc: 0.7073\n","\n","Epoch 00024: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.24.hdf5\n","Epoch 25/100\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.8149 - tp: 16132.1875 - fp: 2686.9688 - tn: 2622.4062 - fn: 6206.2188 - accuracy: 0.6783 - precision: 0.8572 - recall: 0.7221 - auc: 0.7136 - val_loss: 0.4578 - val_tp: 16580.0000 - val_fp: 2713.5000 - val_tn: 2702.5000 - val_fn: 6217.2500 - val_accuracy: 0.6835 - val_precision: 0.8594 - val_recall: 0.7273 - val_auc: 0.7192\n","\n","Epoch 00025: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.25.hdf5\n","Epoch 26/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.8016 - tp: 17024.6562 - fp: 2731.1250 - tn: 2795.2500 - fn: 6226.7500 - accuracy: 0.6887 - precision: 0.8617 - recall: 0.7322 - auc: 0.7251 - val_loss: 0.4528 - val_tp: 17473.0000 - val_fp: 2756.5000 - val_tn: 2876.5000 - val_fn: 6237.2500 - val_accuracy: 0.6935 - val_precision: 0.8637 - val_recall: 0.7369 - val_auc: 0.7304\n","\n","Epoch 00026: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.26.hdf5\n","Epoch 27/100\n","1017/1017 [==============================] - 0s 143us/step - loss: 0.7885 - tp: 17918.0000 - fp: 2773.5312 - tn: 2969.8438 - fn: 6246.4062 - accuracy: 0.6984 - precision: 0.8659 - recall: 0.7415 - auc: 0.7360 - val_loss: 0.4481 - val_tp: 18367.0000 - val_fp: 2797.5000 - val_tn: 3052.5000 - val_fn: 6256.2500 - val_accuracy: 0.7029 - val_precision: 0.8678 - val_recall: 0.7459 - val_auc: 0.7409\n","\n","Epoch 00027: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.27.hdf5\n","Epoch 28/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.7758 - tp: 18812.1250 - fp: 2813.4062 - tn: 3146.9688 - fn: 6265.2812 - accuracy: 0.7075 - precision: 0.8699 - recall: 0.7501 - auc: 0.7462 - val_loss: 0.4437 - val_tp: 19261.0000 - val_fp: 2835.5000 - val_tn: 3231.5000 - val_fn: 6275.2500 - val_accuracy: 0.7117 - val_precision: 0.8717 - val_recall: 0.7543 - val_auc: 0.7509\n","\n","Epoch 00028: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.28.hdf5\n","Epoch 29/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.7633 - tp: 19707.8125 - fp: 2849.5938 - tn: 3327.7812 - fn: 6282.5938 - accuracy: 0.7161 - precision: 0.8737 - recall: 0.7583 - auc: 0.7558 - val_loss: 0.4395 - val_tp: 20157.0000 - val_fp: 2869.5000 - val_tn: 3414.5000 - val_fn: 6292.2500 - val_accuracy: 0.7201 - val_precision: 0.8754 - val_recall: 0.7621 - val_auc: 0.7602\n","\n","Epoch 00029: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.29.hdf5\n","Epoch 30/100\n","1017/1017 [==============================] - 0s 146us/step - loss: 0.7511 - tp: 20603.8125 - fp: 2881.9062 - tn: 3512.4688 - fn: 6299.5938 - accuracy: 0.7242 - precision: 0.8773 - recall: 0.7658 - auc: 0.7649 - val_loss: 0.4355 - val_tp: 21053.0000 - val_fp: 2898.5000 - val_tn: 3602.5000 - val_fn: 6309.2500 - val_accuracy: 0.7281 - val_precision: 0.8790 - val_recall: 0.7694 - val_auc: 0.7691\n","\n","Epoch 00030: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.30.hdf5\n","Epoch 31/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.7392 - tp: 21501.3750 - fp: 2908.9375 - tn: 3702.4375 - fn: 6315.0312 - accuracy: 0.7321 - precision: 0.8808 - recall: 0.7730 - auc: 0.7736 - val_loss: 0.4317 - val_tp: 21951.0000 - val_fp: 2923.5000 - val_tn: 3794.5000 - val_fn: 6324.2500 - val_accuracy: 0.7357 - val_precision: 0.8825 - val_recall: 0.7763 - val_auc: 0.7775\n","\n","Epoch 00031: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.31.hdf5\n","Epoch 32/100\n","1017/1017 [==============================] - 0s 130us/step - loss: 0.7275 - tp: 22399.3750 - fp: 2933.9375 - tn: 3894.4375 - fn: 6330.0312 - accuracy: 0.7395 - precision: 0.8842 - recall: 0.7797 - auc: 0.7818 - val_loss: 0.4282 - val_tp: 22849.0000 - val_fp: 2948.5000 - val_tn: 3986.5000 - val_fn: 6339.2500 - val_accuracy: 0.7429 - val_precision: 0.8857 - val_recall: 0.7828 - val_auc: 0.7855\n","\n","Epoch 00032: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.32.hdf5\n","Epoch 33/100\n","1017/1017 [==============================] - 0s 143us/step - loss: 0.7161 - tp: 23297.3750 - fp: 2956.7500 - tn: 4088.6250 - fn: 6345.0312 - accuracy: 0.7464 - precision: 0.8874 - recall: 0.7859 - auc: 0.7895 - val_loss: 0.4248 - val_tp: 23747.0000 - val_fp: 2970.5000 - val_tn: 4181.5000 - val_fn: 6354.2500 - val_accuracy: 0.7497 - val_precision: 0.8888 - val_recall: 0.7889 - val_auc: 0.7931\n","\n","Epoch 00033: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.33.hdf5\n","Epoch 34/100\n","1017/1017 [==============================] - 0s 157us/step - loss: 0.7049 - tp: 24195.3750 - fp: 2978.7500 - tn: 4283.6250 - fn: 6360.0312 - accuracy: 0.7530 - precision: 0.8904 - recall: 0.7918 - auc: 0.7969 - val_loss: 0.4215 - val_tp: 24645.0000 - val_fp: 2992.5000 - val_tn: 4376.5000 - val_fn: 6369.2500 - val_accuracy: 0.7561 - val_precision: 0.8917 - val_recall: 0.7946 - val_auc: 0.8003\n","\n","Epoch 00034: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.34.hdf5\n","Epoch 35/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.6939 - tp: 25094.2188 - fp: 3000.7500 - tn: 4478.6250 - fn: 6374.1875 - accuracy: 0.7593 - precision: 0.8932 - recall: 0.7974 - auc: 0.8040 - val_loss: 0.4185 - val_tp: 25544.0000 - val_fp: 3014.5000 - val_tn: 4571.5000 - val_fn: 6383.2500 - val_accuracy: 0.7622 - val_precision: 0.8944 - val_recall: 0.8001 - val_auc: 0.8071\n","\n","Epoch 00035: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.35.hdf5\n","Epoch 36/100\n","1017/1017 [==============================] - 0s 144us/step - loss: 0.6832 - tp: 25993.2188 - fp: 3021.8125 - tn: 4674.5625 - fn: 6388.1875 - accuracy: 0.7652 - precision: 0.8958 - recall: 0.8027 - auc: 0.8107 - val_loss: 0.4156 - val_tp: 26443.0000 - val_fp: 3034.5000 - val_tn: 4768.5000 - val_fn: 6397.2500 - val_accuracy: 0.7679 - val_precision: 0.8971 - val_recall: 0.8052 - val_auc: 0.8137\n","\n","Epoch 00036: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.36.hdf5\n","Epoch 37/100\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.6727 - tp: 26892.2188 - fp: 3041.8125 - tn: 4871.5625 - fn: 6402.1875 - accuracy: 0.7708 - precision: 0.8984 - recall: 0.8077 - auc: 0.8170 - val_loss: 0.4128 - val_tp: 27342.0000 - val_fp: 3054.5000 - val_tn: 4965.5000 - val_fn: 6411.2500 - val_accuracy: 0.7734 - val_precision: 0.8995 - val_recall: 0.8101 - val_auc: 0.8199\n","\n","Epoch 00037: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.37.hdf5\n","Epoch 38/100\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.6623 - tp: 27792.0625 - fp: 3061.8125 - tn: 5068.5625 - fn: 6415.3438 - accuracy: 0.7761 - precision: 0.9008 - recall: 0.8124 - auc: 0.8231 - val_loss: 0.4101 - val_tp: 28242.0000 - val_fp: 3074.5000 - val_tn: 5162.5000 - val_fn: 6424.2500 - val_accuracy: 0.7786 - val_precision: 0.9018 - val_recall: 0.8147 - val_auc: 0.8258\n","\n","Epoch 00038: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.38.hdf5\n","Epoch 39/100\n","1017/1017 [==============================] - 0s 139us/step - loss: 0.6522 - tp: 28692.0625 - fp: 3081.8125 - tn: 5265.5625 - fn: 6428.3438 - accuracy: 0.7812 - precision: 0.9030 - recall: 0.8170 - auc: 0.8289 - val_loss: 0.4076 - val_tp: 29142.0000 - val_fp: 3094.5000 - val_tn: 5359.5000 - val_fn: 6437.2500 - val_accuracy: 0.7835 - val_precision: 0.9040 - val_recall: 0.8191 - val_auc: 0.8315\n","\n","Epoch 00039: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.39.hdf5\n","Epoch 40/100\n","1017/1017 [==============================] - 0s 150us/step - loss: 0.6423 - tp: 29592.0625 - fp: 3101.8125 - tn: 5462.5625 - fn: 6441.3438 - accuracy: 0.7860 - precision: 0.9051 - recall: 0.8212 - auc: 0.8344 - val_loss: 0.4051 - val_tp: 30042.0000 - val_fp: 3114.5000 - val_tn: 5556.5000 - val_fn: 6450.2500 - val_accuracy: 0.7882 - val_precision: 0.9061 - val_recall: 0.8232 - val_auc: 0.8369\n","\n","Epoch 00040: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.40.hdf5\n","Epoch 41/100\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.6325 - tp: 30492.0625 - fp: 3121.8125 - tn: 5659.5625 - fn: 6454.3438 - accuracy: 0.7906 - precision: 0.9071 - recall: 0.8253 - auc: 0.8397 - val_loss: 0.4028 - val_tp: 30942.0000 - val_fp: 3134.5000 - val_tn: 5753.5000 - val_fn: 6463.2500 - val_accuracy: 0.7927 - val_precision: 0.9080 - val_recall: 0.8272 - val_auc: 0.8421\n","\n","Epoch 00041: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.41.hdf5\n","Epoch 42/100\n","1017/1017 [==============================] - 0s 146us/step - loss: 0.6230 - tp: 31392.0625 - fp: 3141.8125 - tn: 5856.5625 - fn: 6467.3438 - accuracy: 0.7949 - precision: 0.9090 - recall: 0.8292 - auc: 0.8448 - val_loss: 0.4006 - val_tp: 31842.0000 - val_fp: 3154.5000 - val_tn: 5950.5000 - val_fn: 6476.2500 - val_accuracy: 0.7969 - val_precision: 0.9099 - val_recall: 0.8310 - val_auc: 0.8470\n","\n","Epoch 00042: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.42.hdf5\n","Epoch 43/100\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.6136 - tp: 32292.0625 - fp: 3161.8125 - tn: 6053.5625 - fn: 6480.3438 - accuracy: 0.7991 - precision: 0.9108 - recall: 0.8329 - auc: 0.8496 - val_loss: 0.3985 - val_tp: 32742.0000 - val_fp: 3174.5000 - val_tn: 6147.5000 - val_fn: 6489.2500 - val_accuracy: 0.8010 - val_precision: 0.9116 - val_recall: 0.8346 - val_auc: 0.8518\n","\n","Epoch 00043: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.43.hdf5\n","Epoch 44/100\n","1017/1017 [==============================] - 0s 139us/step - loss: 0.6044 - tp: 33192.0625 - fp: 3181.1875 - tn: 6251.1875 - fn: 6493.3438 - accuracy: 0.8030 - precision: 0.9125 - recall: 0.8364 - auc: 0.8543 - val_loss: 0.3965 - val_tp: 33642.0000 - val_fp: 3192.5000 - val_tn: 6346.5000 - val_fn: 6502.2500 - val_accuracy: 0.8049 - val_precision: 0.9133 - val_recall: 0.8380 - val_auc: 0.8563\n","\n","Epoch 00044: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.44.hdf5\n","Epoch 45/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.5954 - tp: 34092.0625 - fp: 3199.1875 - tn: 6450.1875 - fn: 6506.3438 - accuracy: 0.8068 - precision: 0.9142 - recall: 0.8397 - auc: 0.8587 - val_loss: 0.3945 - val_tp: 34542.0000 - val_fp: 3210.5000 - val_tn: 6545.5000 - val_fn: 6515.2500 - val_accuracy: 0.8086 - val_precision: 0.9150 - val_recall: 0.8413 - val_auc: 0.8606\n","\n","Epoch 00045: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.45.hdf5\n","Epoch 46/100\n","1017/1017 [==============================] - 0s 153us/step - loss: 0.5866 - tp: 34992.0625 - fp: 3217.1875 - tn: 6649.1875 - fn: 6519.3438 - accuracy: 0.8105 - precision: 0.9158 - recall: 0.8429 - auc: 0.8629 - val_loss: 0.3927 - val_tp: 35442.0000 - val_fp: 3228.5000 - val_tn: 6744.5000 - val_fn: 6528.2500 - val_accuracy: 0.8122 - val_precision: 0.9165 - val_recall: 0.8445 - val_auc: 0.8648\n","\n","Epoch 00046: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.46.hdf5\n","Epoch 47/100\n","1017/1017 [==============================] - 0s 146us/step - loss: 0.5779 - tp: 35892.0625 - fp: 3233.5625 - tn: 6849.8125 - fn: 6532.3438 - accuracy: 0.8140 - precision: 0.9174 - recall: 0.8460 - auc: 0.8670 - val_loss: 0.3909 - val_tp: 36342.0000 - val_fp: 3243.5000 - val_tn: 6946.5000 - val_fn: 6541.2500 - val_accuracy: 0.8156 - val_precision: 0.9181 - val_recall: 0.8475 - val_auc: 0.8688\n","\n","Epoch 00047: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.47.hdf5\n","Epoch 48/100\n","1017/1017 [==============================] - 0s 151us/step - loss: 0.5694 - tp: 36792.0625 - fp: 3247.5938 - tn: 7052.7812 - fn: 6545.3438 - accuracy: 0.8174 - precision: 0.9189 - recall: 0.8490 - auc: 0.8709 - val_loss: 0.3892 - val_tp: 37242.0000 - val_fp: 3257.5000 - val_tn: 7149.5000 - val_fn: 6554.2500 - val_accuracy: 0.8190 - val_precision: 0.9196 - val_recall: 0.8503 - val_auc: 0.8726\n","\n","Epoch 00048: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.48.hdf5\n","Epoch 49/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.5610 - tp: 37692.0625 - fp: 3261.4688 - tn: 7255.9062 - fn: 6558.3438 - accuracy: 0.8207 - precision: 0.9204 - recall: 0.8518 - auc: 0.8746 - val_loss: 0.3875 - val_tp: 38142.0000 - val_fp: 3271.5000 - val_tn: 7352.5000 - val_fn: 6567.2500 - val_accuracy: 0.8222 - val_precision: 0.9210 - val_recall: 0.8531 - val_auc: 0.8762\n","\n","Epoch 00049: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.49.hdf5\n","Epoch 50/100\n","1017/1017 [==============================] - 0s 145us/step - loss: 0.5528 - tp: 38592.3750 - fp: 3275.4688 - tn: 7458.9062 - fn: 6571.0312 - accuracy: 0.8238 - precision: 0.9218 - recall: 0.8545 - auc: 0.8782 - val_loss: 0.3860 - val_tp: 39043.0000 - val_fp: 3285.5000 - val_tn: 7555.5000 - val_fn: 6579.2500 - val_accuracy: 0.8253 - val_precision: 0.9224 - val_recall: 0.8558 - val_auc: 0.8797\n","\n","Epoch 00050: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.50.hdf5\n","Epoch 51/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.5447 - tp: 39493.3750 - fp: 3289.4688 - tn: 7661.9062 - fn: 6583.0312 - accuracy: 0.8269 - precision: 0.9231 - recall: 0.8571 - auc: 0.8816 - val_loss: 0.3845 - val_tp: 39944.0000 - val_fp: 3299.5000 - val_tn: 7758.5000 - val_fn: 6591.2500 - val_accuracy: 0.8283 - val_precision: 0.9237 - val_recall: 0.8584 - val_auc: 0.8831\n","\n","Epoch 00051: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.51.hdf5\n","Epoch 52/100\n","1017/1017 [==============================] - 0s 138us/step - loss: 0.5368 - tp: 40394.3750 - fp: 3303.4688 - tn: 7864.9062 - fn: 6595.0312 - accuracy: 0.8298 - precision: 0.9244 - recall: 0.8596 - auc: 0.8849 - val_loss: 0.3830 - val_tp: 40845.0000 - val_fp: 3313.7500 - val_tn: 7961.2500 - val_fn: 6603.2500 - val_accuracy: 0.8311 - val_precision: 0.9250 - val_recall: 0.8608 - val_auc: 0.8863\n","\n","Epoch 00052: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.52.hdf5\n","Epoch 53/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.5290 - tp: 41295.3750 - fp: 3317.4688 - tn: 8067.9062 - fn: 6607.0312 - accuracy: 0.8326 - precision: 0.9256 - recall: 0.8621 - auc: 0.8880 - val_loss: 0.3817 - val_tp: 41746.0000 - val_fp: 3327.7500 - val_tn: 8164.2500 - val_fn: 6615.2500 - val_accuracy: 0.8339 - val_precision: 0.9262 - val_recall: 0.8632 - val_auc: 0.8893\n","\n","Epoch 00053: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.53.hdf5\n","Epoch 54/100\n","1017/1017 [==============================] - 0s 147us/step - loss: 0.5214 - tp: 42196.3750 - fp: 3331.4688 - tn: 8270.9062 - fn: 6619.0312 - accuracy: 0.8353 - precision: 0.9268 - recall: 0.8644 - auc: 0.8910 - val_loss: 0.3803 - val_tp: 42647.0000 - val_fp: 3341.7500 - val_tn: 8367.2500 - val_fn: 6627.2500 - val_accuracy: 0.8365 - val_precision: 0.9273 - val_recall: 0.8655 - val_auc: 0.8923\n","\n","Epoch 00054: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.54.hdf5\n","Epoch 55/100\n","1017/1017 [==============================] - 0s 127us/step - loss: 0.5139 - tp: 43097.3750 - fp: 3345.4688 - tn: 8473.9062 - fn: 6631.0312 - accuracy: 0.8379 - precision: 0.9280 - recall: 0.8667 - auc: 0.8938 - val_loss: 0.3791 - val_tp: 43548.0000 - val_fp: 3355.7500 - val_tn: 8570.2500 - val_fn: 6639.2500 - val_accuracy: 0.8391 - val_precision: 0.9285 - val_recall: 0.8677 - val_auc: 0.8951\n","\n","Epoch 00055: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.55.hdf5\n","Epoch 56/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.5065 - tp: 43998.3750 - fp: 3359.4688 - tn: 8676.9062 - fn: 6643.0312 - accuracy: 0.8404 - precision: 0.9291 - recall: 0.8688 - auc: 0.8966 - val_loss: 0.3779 - val_tp: 44449.0000 - val_fp: 3369.7500 - val_tn: 8773.2500 - val_fn: 6651.2500 - val_accuracy: 0.8415 - val_precision: 0.9295 - val_recall: 0.8698 - val_auc: 0.8978\n","\n","Epoch 00056: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.56.hdf5\n","Epoch 57/100\n","1017/1017 [==============================] - 0s 146us/step - loss: 0.4993 - tp: 44899.3750 - fp: 3373.4688 - tn: 8879.9062 - fn: 6655.0312 - accuracy: 0.8428 - precision: 0.9301 - recall: 0.8709 - auc: 0.8992 - val_loss: 0.3767 - val_tp: 45350.0000 - val_fp: 3383.7500 - val_tn: 8976.2500 - val_fn: 6663.2500 - val_accuracy: 0.8439 - val_precision: 0.9306 - val_recall: 0.8719 - val_auc: 0.9003\n","\n","Epoch 00057: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.57.hdf5\n","Epoch 58/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.4922 - tp: 45800.3750 - fp: 3387.4688 - tn: 9082.9062 - fn: 6667.0312 - accuracy: 0.8452 - precision: 0.9311 - recall: 0.8729 - auc: 0.9017 - val_loss: 0.3756 - val_tp: 46251.0000 - val_fp: 3397.7500 - val_tn: 9179.2500 - val_fn: 6675.2500 - val_accuracy: 0.8462 - val_precision: 0.9316 - val_recall: 0.8739 - val_auc: 0.9028\n","\n","Epoch 00058: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.58.hdf5\n","Epoch 59/100\n","1017/1017 [==============================] - 0s 131us/step - loss: 0.4852 - tp: 46701.3750 - fp: 3401.4688 - tn: 9285.9062 - fn: 6679.0312 - accuracy: 0.8474 - precision: 0.9321 - recall: 0.8749 - auc: 0.9041 - val_loss: 0.3745 - val_tp: 47152.0000 - val_fp: 3411.7500 - val_tn: 9382.2500 - val_fn: 6687.2500 - val_accuracy: 0.8484 - val_precision: 0.9325 - val_recall: 0.8758 - val_auc: 0.9052\n","\n","Epoch 00059: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.59.hdf5\n","Epoch 60/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.4783 - tp: 47602.3750 - fp: 3415.4688 - tn: 9488.9062 - fn: 6691.0312 - accuracy: 0.8496 - precision: 0.9331 - recall: 0.8768 - auc: 0.9064 - val_loss: 0.3735 - val_tp: 48053.0000 - val_fp: 3425.7500 - val_tn: 9585.2500 - val_fn: 6699.2500 - val_accuracy: 0.8506 - val_precision: 0.9335 - val_recall: 0.8776 - val_auc: 0.9074\n","\n","Epoch 00060: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.60.hdf5\n","Epoch 61/100\n","1017/1017 [==============================] - 0s 149us/step - loss: 0.4716 - tp: 48503.3750 - fp: 3429.4688 - tn: 9691.9062 - fn: 6703.0312 - accuracy: 0.8517 - precision: 0.9340 - recall: 0.8786 - auc: 0.9087 - val_loss: 0.3726 - val_tp: 48954.0000 - val_fp: 3439.7500 - val_tn: 9788.2500 - val_fn: 6711.2500 - val_accuracy: 0.8527 - val_precision: 0.9343 - val_recall: 0.8794 - val_auc: 0.9096\n","\n","Epoch 00061: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.61.hdf5\n","Epoch 62/100\n","1017/1017 [==============================] - 0s 153us/step - loss: 0.4650 - tp: 49404.3750 - fp: 3443.4688 - tn: 9894.9062 - fn: 6715.0312 - accuracy: 0.8537 - precision: 0.9348 - recall: 0.8803 - auc: 0.9108 - val_loss: 0.3716 - val_tp: 49855.0000 - val_fp: 3453.7500 - val_tn: 9991.2500 - val_fn: 6723.2500 - val_accuracy: 0.8547 - val_precision: 0.9352 - val_recall: 0.8812 - val_auc: 0.9117\n","\n","Epoch 00062: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.62.hdf5\n","Epoch 63/100\n","1017/1017 [==============================] - 0s 131us/step - loss: 0.4585 - tp: 50305.3750 - fp: 3457.4688 - tn: 10097.9062 - fn: 6727.0312 - accuracy: 0.8557 - precision: 0.9357 - recall: 0.8820 - auc: 0.9128 - val_loss: 0.3707 - val_tp: 50756.0000 - val_fp: 3467.7500 - val_tn: 10194.2500 - val_fn: 6735.2500 - val_accuracy: 0.8566 - val_precision: 0.9360 - val_recall: 0.8828 - val_auc: 0.9137\n","\n","Epoch 00063: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.63.hdf5\n","Epoch 64/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.4521 - tp: 51206.3750 - fp: 3471.4688 - tn: 10300.9062 - fn: 6739.0312 - accuracy: 0.8576 - precision: 0.9365 - recall: 0.8837 - auc: 0.9148 - val_loss: 0.3699 - val_tp: 51657.0000 - val_fp: 3481.7500 - val_tn: 10397.2500 - val_fn: 6747.2500 - val_accuracy: 0.8585 - val_precision: 0.9369 - val_recall: 0.8845 - val_auc: 0.9156\n","\n","Epoch 00064: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.64.hdf5\n","Epoch 65/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.4458 - tp: 52107.3750 - fp: 3485.4688 - tn: 10503.9062 - fn: 6751.0312 - accuracy: 0.8595 - precision: 0.9373 - recall: 0.8853 - auc: 0.9167 - val_loss: 0.3691 - val_tp: 52557.2500 - val_fp: 3495.7500 - val_tn: 10600.2500 - val_fn: 6760.0000 - val_accuracy: 0.8603 - val_precision: 0.9376 - val_recall: 0.8860 - val_auc: 0.9174\n","\n","Epoch 00065: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.65.hdf5\n","Epoch 66/100\n","1017/1017 [==============================] - 0s 141us/step - loss: 0.4396 - tp: 53007.3750 - fp: 3499.4688 - tn: 10706.9062 - fn: 6764.0312 - accuracy: 0.8613 - precision: 0.9381 - recall: 0.8868 - auc: 0.9185 - val_loss: 0.3683 - val_tp: 53457.2500 - val_fp: 3509.7500 - val_tn: 10803.2500 - val_fn: 6773.0000 - val_accuracy: 0.8621 - val_precision: 0.9384 - val_recall: 0.8875 - val_auc: 0.9192\n","\n","Epoch 00066: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.66.hdf5\n","Epoch 67/100\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.4336 - tp: 53907.3750 - fp: 3513.4688 - tn: 10909.9062 - fn: 6777.0312 - accuracy: 0.8630 - precision: 0.9388 - recall: 0.8883 - auc: 0.9202 - val_loss: 0.3676 - val_tp: 54357.2500 - val_fp: 3523.7500 - val_tn: 11006.2500 - val_fn: 6786.0000 - val_accuracy: 0.8638 - val_precision: 0.9391 - val_recall: 0.8890 - val_auc: 0.9209\n","\n","Epoch 00067: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.67.hdf5\n","Epoch 68/100\n","1017/1017 [==============================] - 0s 154us/step - loss: 0.4276 - tp: 54807.3750 - fp: 3527.4688 - tn: 11112.9062 - fn: 6790.0312 - accuracy: 0.8647 - precision: 0.9395 - recall: 0.8898 - auc: 0.9219 - val_loss: 0.3669 - val_tp: 55257.2500 - val_fp: 3537.7500 - val_tn: 11209.2500 - val_fn: 6799.0000 - val_accuracy: 0.8654 - val_precision: 0.9398 - val_recall: 0.8904 - val_auc: 0.9226\n","\n","Epoch 00068: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.68.hdf5\n","Epoch 69/100\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.4218 - tp: 55707.3750 - fp: 3541.0000 - tn: 11316.3750 - fn: 6803.0312 - accuracy: 0.8663 - precision: 0.9402 - recall: 0.8912 - auc: 0.9235 - val_loss: 0.3662 - val_tp: 56157.2500 - val_fp: 3550.7500 - val_tn: 11413.2500 - val_fn: 6812.0000 - val_accuracy: 0.8670 - val_precision: 0.9405 - val_recall: 0.8918 - val_auc: 0.9241\n","\n","Epoch 00069: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.69.hdf5\n","Epoch 70/100\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.4160 - tp: 56607.3750 - fp: 3554.0000 - tn: 11520.3750 - fn: 6816.0312 - accuracy: 0.8679 - precision: 0.9409 - recall: 0.8925 - auc: 0.9250 - val_loss: 0.3656 - val_tp: 57057.2500 - val_fp: 3563.7500 - val_tn: 11617.2500 - val_fn: 6825.0000 - val_accuracy: 0.8686 - val_precision: 0.9412 - val_recall: 0.8932 - val_auc: 0.9256\n","\n","Epoch 00070: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.70.hdf5\n","Epoch 71/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.4104 - tp: 57507.3750 - fp: 3567.0000 - tn: 11724.3750 - fn: 6829.0312 - accuracy: 0.8694 - precision: 0.9416 - recall: 0.8939 - auc: 0.9265 - val_loss: 0.3650 - val_tp: 57957.2500 - val_fp: 3576.7500 - val_tn: 11821.2500 - val_fn: 6838.0000 - val_accuracy: 0.8701 - val_precision: 0.9419 - val_recall: 0.8945 - val_auc: 0.9271\n","\n","Epoch 00071: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.71.hdf5\n","Epoch 72/100\n","1017/1017 [==============================] - 0s 167us/step - loss: 0.4048 - tp: 58407.3750 - fp: 3580.0000 - tn: 11928.3750 - fn: 6842.0312 - accuracy: 0.8709 - precision: 0.9422 - recall: 0.8951 - auc: 0.9279 - val_loss: 0.3644 - val_tp: 58857.2500 - val_fp: 3589.7500 - val_tn: 12025.2500 - val_fn: 6851.0000 - val_accuracy: 0.8716 - val_precision: 0.9425 - val_recall: 0.8957 - val_auc: 0.9285\n","\n","Epoch 00072: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.72.hdf5\n","Epoch 73/100\n","1017/1017 [==============================] - 0s 130us/step - loss: 0.3993 - tp: 59307.3750 - fp: 3593.0000 - tn: 12132.3750 - fn: 6855.0312 - accuracy: 0.8724 - precision: 0.9429 - recall: 0.8964 - auc: 0.9293 - val_loss: 0.3639 - val_tp: 59757.2500 - val_fp: 3602.7500 - val_tn: 12229.2500 - val_fn: 6864.0000 - val_accuracy: 0.8731 - val_precision: 0.9431 - val_recall: 0.8970 - val_auc: 0.9298\n","\n","Epoch 00073: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.73.hdf5\n","Epoch 74/100\n","1017/1017 [==============================] - 0s 145us/step - loss: 0.3940 - tp: 60207.3750 - fp: 3606.0000 - tn: 12336.3750 - fn: 6868.0312 - accuracy: 0.8738 - precision: 0.9435 - recall: 0.8976 - auc: 0.9306 - val_loss: 0.3634 - val_tp: 60657.2500 - val_fp: 3615.7500 - val_tn: 12433.2500 - val_fn: 6877.0000 - val_accuracy: 0.8745 - val_precision: 0.9437 - val_recall: 0.8982 - val_auc: 0.9311\n","\n","Epoch 00074: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.74.hdf5\n","Epoch 75/100\n","1017/1017 [==============================] - 0s 142us/step - loss: 0.3887 - tp: 61107.3750 - fp: 3619.0000 - tn: 12540.3750 - fn: 6881.0312 - accuracy: 0.8752 - precision: 0.9441 - recall: 0.8988 - auc: 0.9319 - val_loss: 0.3629 - val_tp: 61557.2500 - val_fp: 3628.7500 - val_tn: 12637.2500 - val_fn: 6890.0000 - val_accuracy: 0.8758 - val_precision: 0.9443 - val_recall: 0.8993 - val_auc: 0.9324\n","\n","Epoch 00075: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.75.hdf5\n","Epoch 76/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.3835 - tp: 62007.3750 - fp: 3632.0000 - tn: 12744.3750 - fn: 6894.0312 - accuracy: 0.8766 - precision: 0.9447 - recall: 0.8999 - auc: 0.9331 - val_loss: 0.3624 - val_tp: 62457.2500 - val_fp: 3641.7500 - val_tn: 12841.2500 - val_fn: 6903.0000 - val_accuracy: 0.8772 - val_precision: 0.9449 - val_recall: 0.9005 - val_auc: 0.9336\n","\n","Epoch 00076: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.76.hdf5\n","Epoch 77/100\n","1017/1017 [==============================] - 0s 142us/step - loss: 0.3784 - tp: 62907.3750 - fp: 3645.0000 - tn: 12948.3750 - fn: 6907.0312 - accuracy: 0.8779 - precision: 0.9452 - recall: 0.9011 - auc: 0.9343 - val_loss: 0.3620 - val_tp: 63357.2500 - val_fp: 3654.7500 - val_tn: 13045.2500 - val_fn: 6916.0000 - val_accuracy: 0.8785 - val_precision: 0.9455 - val_recall: 0.9016 - val_auc: 0.9348\n","\n","Epoch 00077: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.77.hdf5\n","Epoch 78/100\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.3733 - tp: 63807.3750 - fp: 3658.0000 - tn: 13152.3750 - fn: 6920.0312 - accuracy: 0.8792 - precision: 0.9458 - recall: 0.9022 - auc: 0.9354 - val_loss: 0.3616 - val_tp: 64257.2500 - val_fp: 3667.7500 - val_tn: 13249.2500 - val_fn: 6929.0000 - val_accuracy: 0.8797 - val_precision: 0.9460 - val_recall: 0.9027 - val_auc: 0.9359\n","\n","Epoch 00078: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.78.hdf5\n","Epoch 79/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.3684 - tp: 64707.3750 - fp: 3671.0000 - tn: 13356.3750 - fn: 6933.0312 - accuracy: 0.8804 - precision: 0.9463 - recall: 0.9032 - auc: 0.9365 - val_loss: 0.3612 - val_tp: 65157.2500 - val_fp: 3680.7500 - val_tn: 13453.2500 - val_fn: 6942.0000 - val_accuracy: 0.8810 - val_precision: 0.9465 - val_recall: 0.9037 - val_auc: 0.9370\n","\n","Epoch 00079: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.79.hdf5\n","Epoch 80/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.3636 - tp: 65607.3750 - fp: 3684.0000 - tn: 13560.3750 - fn: 6946.0312 - accuracy: 0.8816 - precision: 0.9468 - recall: 0.9043 - auc: 0.9376 - val_loss: 0.3609 - val_tp: 66058.2500 - val_fp: 3693.7500 - val_tn: 13657.2500 - val_fn: 6954.0000 - val_accuracy: 0.8822 - val_precision: 0.9470 - val_recall: 0.9048 - val_auc: 0.9380\n","\n","Epoch 00080: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.80.hdf5\n","Epoch 81/100\n","1017/1017 [==============================] - 0s 146us/step - loss: 0.3588 - tp: 66508.3750 - fp: 3697.0000 - tn: 13764.3750 - fn: 6958.0312 - accuracy: 0.8828 - precision: 0.9473 - recall: 0.9053 - auc: 0.9386 - val_loss: 0.3605 - val_tp: 66959.2500 - val_fp: 3706.7500 - val_tn: 13861.2500 - val_fn: 6966.0000 - val_accuracy: 0.8833 - val_precision: 0.9475 - val_recall: 0.9058 - val_auc: 0.9390\n","\n","Epoch 00081: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.81.hdf5\n","Epoch 82/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.3541 - tp: 67409.3750 - fp: 3710.0000 - tn: 13968.3750 - fn: 6970.0312 - accuracy: 0.8840 - precision: 0.9478 - recall: 0.9063 - auc: 0.9396 - val_loss: 0.3602 - val_tp: 67860.2500 - val_fp: 3719.7500 - val_tn: 14065.2500 - val_fn: 6978.0000 - val_accuracy: 0.8845 - val_precision: 0.9480 - val_recall: 0.9068 - val_auc: 0.9400\n","\n","Epoch 00082: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.82.hdf5\n","Epoch 83/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.3495 - tp: 68310.3750 - fp: 3723.0000 - tn: 14172.3750 - fn: 6982.0312 - accuracy: 0.8851 - precision: 0.9483 - recall: 0.9073 - auc: 0.9406 - val_loss: 0.3600 - val_tp: 68760.2500 - val_fp: 3732.7500 - val_tn: 14269.2500 - val_fn: 6991.0000 - val_accuracy: 0.8856 - val_precision: 0.9485 - val_recall: 0.9077 - val_auc: 0.9409\n","\n","Epoch 00083: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.83.hdf5\n","Epoch 84/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.3449 - tp: 69210.3750 - fp: 3736.0000 - tn: 14376.3750 - fn: 6995.0312 - accuracy: 0.8862 - precision: 0.9488 - recall: 0.9082 - auc: 0.9415 - val_loss: 0.3597 - val_tp: 69660.2500 - val_fp: 3745.7500 - val_tn: 14473.2500 - val_fn: 7004.0000 - val_accuracy: 0.8867 - val_precision: 0.9490 - val_recall: 0.9086 - val_auc: 0.9419\n","\n","Epoch 00084: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.84.hdf5\n","Epoch 85/100\n","1017/1017 [==============================] - 0s 152us/step - loss: 0.3404 - tp: 70110.3750 - fp: 3749.0000 - tn: 14580.3750 - fn: 7008.0312 - accuracy: 0.8873 - precision: 0.9492 - recall: 0.9091 - auc: 0.9424 - val_loss: 0.3595 - val_tp: 70560.2500 - val_fp: 3758.7500 - val_tn: 14677.2500 - val_fn: 7017.0000 - val_accuracy: 0.8878 - val_precision: 0.9494 - val_recall: 0.9095 - val_auc: 0.9427\n","\n","Epoch 00085: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.85.hdf5\n","Epoch 86/100\n","1017/1017 [==============================] - 0s 139us/step - loss: 0.3360 - tp: 71010.3750 - fp: 3762.0000 - tn: 14784.3750 - fn: 7021.0312 - accuracy: 0.8883 - precision: 0.9497 - recall: 0.9100 - auc: 0.9433 - val_loss: 0.3593 - val_tp: 71460.2500 - val_fp: 3771.7500 - val_tn: 14881.2500 - val_fn: 7030.0000 - val_accuracy: 0.8888 - val_precision: 0.9499 - val_recall: 0.9104 - val_auc: 0.9436\n","\n","Epoch 00086: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.86.hdf5\n","Epoch 87/100\n","1017/1017 [==============================] - 0s 138us/step - loss: 0.3317 - tp: 71910.3750 - fp: 3775.0000 - tn: 14988.3750 - fn: 7034.0312 - accuracy: 0.8894 - precision: 0.9501 - recall: 0.9109 - auc: 0.9441 - val_loss: 0.3591 - val_tp: 72360.2500 - val_fp: 3784.7500 - val_tn: 15085.2500 - val_fn: 7043.0000 - val_accuracy: 0.8898 - val_precision: 0.9503 - val_recall: 0.9113 - val_auc: 0.9444\n","\n","Epoch 00087: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.87.hdf5\n","Epoch 88/100\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.3275 - tp: 72810.3750 - fp: 3788.0000 - tn: 15192.3750 - fn: 7047.0312 - accuracy: 0.8904 - precision: 0.9505 - recall: 0.9118 - auc: 0.9449 - val_loss: 0.3589 - val_tp: 73260.2500 - val_fp: 3797.7500 - val_tn: 15289.2500 - val_fn: 7056.0000 - val_accuracy: 0.8908 - val_precision: 0.9507 - val_recall: 0.9121 - val_auc: 0.9452\n","\n","Epoch 00088: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.88.hdf5\n","Epoch 89/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.3233 - tp: 73710.3750 - fp: 3801.0000 - tn: 15396.3750 - fn: 7060.0312 - accuracy: 0.8914 - precision: 0.9510 - recall: 0.9126 - auc: 0.9457 - val_loss: 0.3588 - val_tp: 74160.2500 - val_fp: 3810.7500 - val_tn: 15493.2500 - val_fn: 7069.0000 - val_accuracy: 0.8918 - val_precision: 0.9511 - val_recall: 0.9130 - val_auc: 0.9460\n","\n","Epoch 00089: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.89.hdf5\n","Epoch 90/100\n","1017/1017 [==============================] - 0s 137us/step - loss: 0.3192 - tp: 74610.3750 - fp: 3814.0000 - tn: 15600.3750 - fn: 7073.0312 - accuracy: 0.8923 - precision: 0.9514 - recall: 0.9134 - auc: 0.9465 - val_loss: 0.3586 - val_tp: 75060.2500 - val_fp: 3823.7500 - val_tn: 15697.2500 - val_fn: 7082.0000 - val_accuracy: 0.8927 - val_precision: 0.9515 - val_recall: 0.9138 - val_auc: 0.9468\n","\n","Epoch 00090: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.90.hdf5\n","Epoch 91/100\n","1017/1017 [==============================] - 0s 141us/step - loss: 0.3151 - tp: 75510.3750 - fp: 3827.0000 - tn: 15804.3750 - fn: 7086.0312 - accuracy: 0.8932 - precision: 0.9518 - recall: 0.9142 - auc: 0.9472 - val_loss: 0.3585 - val_tp: 75960.2500 - val_fp: 3836.7500 - val_tn: 15901.2500 - val_fn: 7095.0000 - val_accuracy: 0.8937 - val_precision: 0.9519 - val_recall: 0.9146 - val_auc: 0.9475\n","\n","Epoch 00091: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.91.hdf5\n","Epoch 92/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.3111 - tp: 76410.3750 - fp: 3840.0000 - tn: 16008.3750 - fn: 7099.0312 - accuracy: 0.8942 - precision: 0.9521 - recall: 0.9150 - auc: 0.9479 - val_loss: 0.3584 - val_tp: 76860.2500 - val_fp: 3849.7500 - val_tn: 16105.2500 - val_fn: 7108.0000 - val_accuracy: 0.8946 - val_precision: 0.9523 - val_recall: 0.9153 - val_auc: 0.9482\n","\n","Epoch 00092: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.92.hdf5\n","Epoch 93/100\n","1017/1017 [==============================] - 0s 147us/step - loss: 0.3072 - tp: 77310.3750 - fp: 3853.0000 - tn: 16212.3750 - fn: 7112.0312 - accuracy: 0.8951 - precision: 0.9525 - recall: 0.9158 - auc: 0.9486 - val_loss: 0.3583 - val_tp: 77760.2500 - val_fp: 3862.7500 - val_tn: 16309.2500 - val_fn: 7121.0000 - val_accuracy: 0.8954 - val_precision: 0.9527 - val_recall: 0.9161 - val_auc: 0.9489\n","\n","Epoch 00093: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.93.hdf5\n","Epoch 94/100\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.3033 - tp: 78210.3750 - fp: 3866.0000 - tn: 16416.3750 - fn: 7125.0312 - accuracy: 0.8959 - precision: 0.9529 - recall: 0.9165 - auc: 0.9493 - val_loss: 0.3583 - val_tp: 78660.2500 - val_fp: 3875.7500 - val_tn: 16513.2500 - val_fn: 7134.0000 - val_accuracy: 0.8963 - val_precision: 0.9530 - val_recall: 0.9168 - val_auc: 0.9495\n","\n","Epoch 00094: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.94.hdf5\n","Epoch 95/100\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.2995 - tp: 79110.3750 - fp: 3879.0000 - tn: 16620.3750 - fn: 7138.0312 - accuracy: 0.8968 - precision: 0.9533 - recall: 0.9172 - auc: 0.9499 - val_loss: 0.3583 - val_tp: 79560.2500 - val_fp: 3888.7500 - val_tn: 16717.2500 - val_fn: 7147.0000 - val_accuracy: 0.8972 - val_precision: 0.9534 - val_recall: 0.9176 - val_auc: 0.9502\n","\n","Epoch 00095: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.95.hdf5\n","Epoch 96/100\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.2958 - tp: 80010.3750 - fp: 3892.0000 - tn: 16824.3750 - fn: 7151.0312 - accuracy: 0.8976 - precision: 0.9536 - recall: 0.9180 - auc: 0.9506 - val_loss: 0.3582 - val_tp: 80460.2500 - val_fp: 3901.7500 - val_tn: 16921.2500 - val_fn: 7160.0000 - val_accuracy: 0.8980 - val_precision: 0.9537 - val_recall: 0.9183 - val_auc: 0.9508\n","\n","Epoch 00096: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.96.hdf5\n","Epoch 97/100\n","1017/1017 [==============================] - 0s 147us/step - loss: 0.2921 - tp: 80910.3750 - fp: 3905.0000 - tn: 17028.3750 - fn: 7164.0312 - accuracy: 0.8985 - precision: 0.9540 - recall: 0.9187 - auc: 0.9512 - val_loss: 0.3582 - val_tp: 81360.2500 - val_fp: 3914.7500 - val_tn: 17125.2500 - val_fn: 7173.0000 - val_accuracy: 0.8988 - val_precision: 0.9541 - val_recall: 0.9190 - val_auc: 0.9514\n","\n","Epoch 00097: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.97.hdf5\n","Epoch 98/100\n","1017/1017 [==============================] - 0s 143us/step - loss: 0.2885 - tp: 81810.3750 - fp: 3918.0000 - tn: 17232.3750 - fn: 7177.0312 - accuracy: 0.8993 - precision: 0.9543 - recall: 0.9193 - auc: 0.9518 - val_loss: 0.3582 - val_tp: 82260.2500 - val_fp: 3927.7500 - val_tn: 17329.2500 - val_fn: 7186.0000 - val_accuracy: 0.8996 - val_precision: 0.9544 - val_recall: 0.9197 - val_auc: 0.9520\n","\n","Epoch 00098: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.98.hdf5\n","Epoch 99/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.2849 - tp: 82710.3750 - fp: 3931.0000 - tn: 17436.3750 - fn: 7190.0312 - accuracy: 0.9001 - precision: 0.9546 - recall: 0.9200 - auc: 0.9524 - val_loss: 0.3583 - val_tp: 83160.2500 - val_fp: 3940.7500 - val_tn: 17533.2500 - val_fn: 7199.0000 - val_accuracy: 0.9004 - val_precision: 0.9548 - val_recall: 0.9203 - val_auc: 0.9526\n","\n","Epoch 00099: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.99.hdf5\n","Epoch 100/100\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.2814 - tp: 83610.3750 - fp: 3944.0000 - tn: 17640.3750 - fn: 7203.0312 - accuracy: 0.9008 - precision: 0.9550 - recall: 0.9207 - auc: 0.9529 - val_loss: 0.3583 - val_tp: 84060.2500 - val_fp: 3953.7500 - val_tn: 17737.2500 - val_fn: 7212.0000 - val_accuracy: 0.9012 - val_precision: 0.9551 - val_recall: 0.9210 - val_auc: 0.9531\n","\n","Epoch 00100: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.100.hdf5\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["<keras.callbacks.callbacks.History at 0x7f09c9cc7898>"]},"metadata":{"tags":[]},"execution_count":45}]},{"cell_type":"code","metadata":{"id":"cZZFc2V8yO1w","colab_type":"code","outputId":"23b18d7c-e553-45f2-98c6-f8d120b75827","executionInfo":{"status":"ok","timestamp":1591117163628,"user_tz":-120,"elapsed":85303,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":52}},"source":["\n","model,cbs = LR_model(0,label = \"abnormal\",modelName=\"inception\");\n","model.load_weights('/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/abnormal/weights.100.hdf5');\n","metrics = model.evaluate(x=x_valid,y=y_valid,verbose=1);\n","print(metrics)"],"execution_count":46,"outputs":[{"output_type":"stream","text":["120/120 [==============================] - 0s 836us/step\n","[0.3410328716039658, 51.0, 13.0, 11.5, 2.5, 0.7601562738418579, 0.7096376419067383, 0.9628891944885254, 0.8675585985183716]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"Vgz7YL67_qfC","colab_type":"text"},"source":["# **ACL**"]},{"cell_type":"code","metadata":{"id":"LtiNB5pjzhP4","colab_type":"code","outputId":"872e08a1-78a6-4df8-988e-899e09dd06f6","executionInfo":{"status":"ok","timestamp":1591117777367,"user_tz":-120,"elapsed":8247,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["# load train, test,  valid data \n","label_type = \"ACL\"\n","exam_view =\"axial\"\n","data_path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/dataset/MRNet-v1.0\"\n","p, l = partition(data_path)\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/train-ACL.csv', newline='') as csvfile:\n","      data_train = list(csv.reader(csvfile))\n","x_train = np.array(data_train,dtype='float32')\n","x_train  = x_train[:,1:4]\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/test-ACL.csv', newline='') as csvfile:\n","      data_test = list(csv.reader(csvfile))\n","x_test = np.array(data_test,dtype='float32')\n","x_test  = x_test[:,1:4]\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/valid-ACL.csv', newline='') as csvfile:\n","      data_valid = list(csv.reader(csvfile))\n","x_valid = np.array(data_valid,dtype='float32')\n","x_valid  = x_valid[:,1:4]\n","\n","# load labels\n","ids_train = sorted(p['train'][exam_view]);\n","ids_test = sorted(p['test'][exam_view]);\n","ids_valid = sorted(p['valid'][exam_view]);\n","\n","arr = [] \n","for e in ids_train:\n","  arr.append(l[e][label_type]);\n","\n","y_train = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","arr = [] \n","for e in ids_test:\n","  arr.append(l[e][label_type]);\n","\n","y_test = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","arr = [] \n","for e in ids_valid:\n","  arr.append(l[e][label_type]);\n","  \n","y_valid = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","# class weight for skewed classes\n","pos = 0\n","for e in p['train'][exam_view]:\n","  if l[e][label_type] == 1:\n","    pos += 1\n","total = len(p['train'][exam_view])\n","neg = total - pos\n","class_weight = {0: 1, 1: neg/pos}\n","if neg < pos:\n","  class_weight = {0: pos/neg, 1: 1}\n","\n","\n","model,cbs = LR_model(0.001,label = \"ACL\",modelName=\"inception\");\n","\n","model.load_weights('/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.100.hdf5');\n","model.fit(x=x_train,y=y_train, validation_data =[x_test,y_test] ,epochs=120, initial_epoch = 100,verbose=1, class_weight=class_weight,callbacks=[cbs[0]],shuffle=False, use_multiprocessing=True, workers=6)"],"execution_count":60,"outputs":[{"output_type":"stream","text":["Train on 1017 samples, validate on 113 samples\n","Epoch 101/120\n","1017/1017 [==============================] - 0s 354us/step - loss: 0.2803 - tp: 105.2812 - fp: 0.7812 - tn: 421.7188 - fn: 0.0000e+00 - accuracy: 0.9986 - precision: 0.9932 - recall: 1.0000 - auc: 1.0000 - val_loss: 0.4169 - val_tp: 201.7500 - val_fp: 9.7500 - val_tn: 878.7500 - val_fn: 3.0000 - val_accuracy: 0.9884 - val_precision: 0.9542 - val_recall: 0.9855 - val_auc: 0.9960\n","\n","Epoch 00101: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.101.hdf5\n","Epoch 102/120\n","1017/1017 [==============================] - 0s 131us/step - loss: 0.2744 - tp: 309.2812 - fp: 13.7812 - tn: 1330.7188 - fn: 4.0000 - accuracy: 0.9890 - precision: 0.9560 - recall: 0.9868 - auc: 0.9964 - val_loss: 0.4149 - val_tp: 405.7500 - val_fp: 22.7500 - val_tn: 1787.7500 - val_fn: 7.0000 - val_accuracy: 0.9866 - val_precision: 0.9470 - val_recall: 0.9831 - val_auc: 0.9953\n","\n","Epoch 00102: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.102.hdf5\n","Epoch 103/120\n","1017/1017 [==============================] - 0s 127us/step - loss: 0.2687 - tp: 513.2812 - fp: 26.7812 - tn: 2239.7188 - fn: 8.0000 - accuracy: 0.9874 - precision: 0.9499 - recall: 0.9845 - auc: 0.9958 - val_loss: 0.4128 - val_tp: 609.7500 - val_fp: 35.7500 - val_tn: 2696.7500 - val_fn: 11.0000 - val_accuracy: 0.9861 - val_precision: 0.9447 - val_recall: 0.9823 - val_auc: 0.9951\n","\n","Epoch 00103: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.103.hdf5\n","Epoch 104/120\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.2631 - tp: 717.2812 - fp: 39.7812 - tn: 3148.7188 - fn: 12.0000 - accuracy: 0.9867 - precision: 0.9472 - recall: 0.9834 - auc: 0.9955 - val_loss: 0.4108 - val_tp: 813.7500 - val_fp: 48.7500 - val_tn: 3605.7500 - val_fn: 15.0000 - val_accuracy: 0.9858 - val_precision: 0.9435 - val_recall: 0.9819 - val_auc: 0.9951\n","\n","Epoch 00104: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.104.hdf5\n","Epoch 105/120\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.2576 - tp: 921.2812 - fp: 52.7812 - tn: 4057.7188 - fn: 16.0000 - accuracy: 0.9863 - precision: 0.9456 - recall: 0.9829 - auc: 0.9954 - val_loss: 0.4087 - val_tp: 1017.7500 - val_fp: 61.7500 - val_tn: 4514.7500 - val_fn: 19.0000 - val_accuracy: 0.9856 - val_precision: 0.9428 - val_recall: 0.9817 - val_auc: 0.9951\n","\n","Epoch 00105: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.105.hdf5\n","Epoch 106/120\n","1017/1017 [==============================] - 0s 138us/step - loss: 0.2523 - tp: 1125.2812 - fp: 65.7812 - tn: 4966.7188 - fn: 20.0000 - accuracy: 0.9861 - precision: 0.9447 - recall: 0.9825 - auc: 0.9953 - val_loss: 0.4066 - val_tp: 1221.7500 - val_fp: 74.7500 - val_tn: 5423.7500 - val_fn: 23.0000 - val_accuracy: 0.9855 - val_precision: 0.9424 - val_recall: 0.9815 - val_auc: 0.9951\n","\n","Epoch 00106: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.106.hdf5\n","Epoch 107/120\n","1017/1017 [==============================] - 0s 145us/step - loss: 0.2472 - tp: 1329.2812 - fp: 78.7812 - tn: 5875.7188 - fn: 24.0000 - accuracy: 0.9859 - precision: 0.9440 - recall: 0.9822 - auc: 0.9953 - val_loss: 0.4044 - val_tp: 1425.7500 - val_fp: 87.7500 - val_tn: 6332.7500 - val_fn: 27.0000 - val_accuracy: 0.9854 - val_precision: 0.9420 - val_recall: 0.9814 - val_auc: 0.9951\n","\n","Epoch 00107: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.107.hdf5\n","Epoch 108/120\n","1017/1017 [==============================] - 0s 139us/step - loss: 0.2423 - tp: 1533.2812 - fp: 91.7812 - tn: 6784.7188 - fn: 28.0000 - accuracy: 0.9858 - precision: 0.9435 - recall: 0.9820 - auc: 0.9953 - val_loss: 0.4023 - val_tp: 1629.7500 - val_fp: 100.7500 - val_tn: 7241.7500 - val_fn: 31.0000 - val_accuracy: 0.9854 - val_precision: 0.9418 - val_recall: 0.9813 - val_auc: 0.9951\n","\n","Epoch 00108: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.108.hdf5\n","Epoch 109/120\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.2375 - tp: 1737.2812 - fp: 104.7812 - tn: 7693.7188 - fn: 32.0000 - accuracy: 0.9857 - precision: 0.9431 - recall: 0.9819 - auc: 0.9953 - val_loss: 0.4002 - val_tp: 1833.7500 - val_fp: 113.7500 - val_tn: 8150.7500 - val_fn: 35.0000 - val_accuracy: 0.9853 - val_precision: 0.9416 - val_recall: 0.9813 - val_auc: 0.9951\n","\n","Epoch 00109: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.109.hdf5\n","Epoch 110/120\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.2328 - tp: 1941.2812 - fp: 117.7812 - tn: 8602.7188 - fn: 36.0000 - accuracy: 0.9856 - precision: 0.9428 - recall: 0.9818 - auc: 0.9953 - val_loss: 0.3981 - val_tp: 2037.7500 - val_fp: 126.7500 - val_tn: 9059.7500 - val_fn: 39.0000 - val_accuracy: 0.9853 - val_precision: 0.9414 - val_recall: 0.9812 - val_auc: 0.9952\n","\n","Epoch 00110: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.110.hdf5\n","Epoch 111/120\n","1017/1017 [==============================] - 0s 136us/step - loss: 0.2283 - tp: 2145.2812 - fp: 130.7812 - tn: 9511.7188 - fn: 40.0000 - accuracy: 0.9856 - precision: 0.9425 - recall: 0.9817 - auc: 0.9953 - val_loss: 0.3960 - val_tp: 2241.7500 - val_fp: 139.7500 - val_tn: 9968.7500 - val_fn: 43.0000 - val_accuracy: 0.9853 - val_precision: 0.9413 - val_recall: 0.9812 - val_auc: 0.9952\n","\n","Epoch 00111: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.111.hdf5\n","Epoch 112/120\n","1017/1017 [==============================] - 0s 118us/step - loss: 0.2239 - tp: 2349.2812 - fp: 143.7812 - tn: 10420.7188 - fn: 44.0000 - accuracy: 0.9855 - precision: 0.9423 - recall: 0.9816 - auc: 0.9954 - val_loss: 0.3940 - val_tp: 2445.7500 - val_fp: 152.7500 - val_tn: 10877.7500 - val_fn: 47.0000 - val_accuracy: 0.9852 - val_precision: 0.9412 - val_recall: 0.9811 - val_auc: 0.9952\n","\n","Epoch 00112: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.112.hdf5\n","Epoch 113/120\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.2196 - tp: 2553.2812 - fp: 156.7812 - tn: 11329.7188 - fn: 48.0000 - accuracy: 0.9855 - precision: 0.9421 - recall: 0.9815 - auc: 0.9954 - val_loss: 0.3919 - val_tp: 2649.7500 - val_fp: 165.7500 - val_tn: 11786.7500 - val_fn: 51.0000 - val_accuracy: 0.9852 - val_precision: 0.9411 - val_recall: 0.9811 - val_auc: 0.9953\n","\n","Epoch 00113: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.113.hdf5\n","Epoch 114/120\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.2154 - tp: 2757.2812 - fp: 169.7812 - tn: 12238.7188 - fn: 52.0000 - accuracy: 0.9854 - precision: 0.9420 - recall: 0.9815 - auc: 0.9954 - val_loss: 0.3899 - val_tp: 2853.7500 - val_fp: 178.7500 - val_tn: 12695.7500 - val_fn: 55.0000 - val_accuracy: 0.9852 - val_precision: 0.9411 - val_recall: 0.9811 - val_auc: 0.9953\n","\n","Epoch 00114: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.114.hdf5\n","Epoch 115/120\n","1017/1017 [==============================] - 0s 141us/step - loss: 0.2114 - tp: 2961.2812 - fp: 182.7812 - tn: 13147.7188 - fn: 56.0000 - accuracy: 0.9854 - precision: 0.9418 - recall: 0.9814 - auc: 0.9954 - val_loss: 0.3879 - val_tp: 3057.7500 - val_fp: 191.7500 - val_tn: 13604.7500 - val_fn: 59.0000 - val_accuracy: 0.9852 - val_precision: 0.9410 - val_recall: 0.9811 - val_auc: 0.9953\n","\n","Epoch 00115: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.115.hdf5\n","Epoch 116/120\n","1017/1017 [==============================] - 0s 128us/step - loss: 0.2074 - tp: 3165.2812 - fp: 195.7812 - tn: 14056.7188 - fn: 60.0000 - accuracy: 0.9854 - precision: 0.9417 - recall: 0.9814 - auc: 0.9954 - val_loss: 0.3860 - val_tp: 3261.7500 - val_fp: 204.7500 - val_tn: 14513.7500 - val_fn: 63.0000 - val_accuracy: 0.9852 - val_precision: 0.9409 - val_recall: 0.9811 - val_auc: 0.9953\n","\n","Epoch 00116: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.116.hdf5\n","Epoch 117/120\n","1017/1017 [==============================] - 0s 129us/step - loss: 0.2036 - tp: 3369.2812 - fp: 208.7812 - tn: 14965.7188 - fn: 64.0000 - accuracy: 0.9853 - precision: 0.9416 - recall: 0.9814 - auc: 0.9954 - val_loss: 0.3841 - val_tp: 3465.7500 - val_fp: 217.7500 - val_tn: 15422.7500 - val_fn: 67.0000 - val_accuracy: 0.9851 - val_precision: 0.9409 - val_recall: 0.9810 - val_auc: 0.9953\n","\n","Epoch 00117: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.117.hdf5\n","Epoch 118/120\n","1017/1017 [==============================] - 0s 132us/step - loss: 0.1999 - tp: 3573.2812 - fp: 221.7812 - tn: 15874.7188 - fn: 68.0000 - accuracy: 0.9853 - precision: 0.9415 - recall: 0.9813 - auc: 0.9955 - val_loss: 0.3822 - val_tp: 3669.7500 - val_fp: 230.7500 - val_tn: 16331.7500 - val_fn: 71.0000 - val_accuracy: 0.9851 - val_precision: 0.9408 - val_recall: 0.9810 - val_auc: 0.9954\n","\n","Epoch 00118: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.118.hdf5\n","Epoch 119/120\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.1962 - tp: 3777.2812 - fp: 234.7812 - tn: 16783.7188 - fn: 72.0000 - accuracy: 0.9853 - precision: 0.9415 - recall: 0.9813 - auc: 0.9955 - val_loss: 0.3803 - val_tp: 3873.7500 - val_fp: 243.7500 - val_tn: 17240.7500 - val_fn: 75.0000 - val_accuracy: 0.9851 - val_precision: 0.9408 - val_recall: 0.9810 - val_auc: 0.9954\n","\n","Epoch 00119: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.119.hdf5\n","Epoch 120/120\n","1017/1017 [==============================] - 0s 146us/step - loss: 0.1927 - tp: 3981.2812 - fp: 247.7812 - tn: 17692.7188 - fn: 76.0000 - accuracy: 0.9853 - precision: 0.9414 - recall: 0.9813 - auc: 0.9955 - val_loss: 0.3785 - val_tp: 4077.7500 - val_fp: 256.7500 - val_tn: 18149.7500 - val_fn: 79.0000 - val_accuracy: 0.9851 - val_precision: 0.9408 - val_recall: 0.9810 - val_auc: 0.9954\n","\n","Epoch 00120: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.120.hdf5\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["<keras.callbacks.callbacks.History at 0x7f09c5ad26a0>"]},"metadata":{"tags":[]},"execution_count":60}]},{"cell_type":"code","metadata":{"id":"FTpB42EkA4Qg","colab_type":"code","outputId":"6698c39b-082b-4d18-e67e-e36b544330ea","executionInfo":{"status":"ok","timestamp":1591117799000,"user_tz":-120,"elapsed":4734,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":52}},"source":["model,cbs = LR_model(0,label = \"ACL\",modelName=\"inception\");\n","model.load_weights('/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/ACL/weights.120.hdf5');\n","metrics = model.evaluate(x=x_valid,y=y_valid,verbose=1);\n","print(metrics)"],"execution_count":61,"outputs":[{"output_type":"stream","text":["120/120 [==============================] - 0s 812us/step\n","[0.5497938672701518, 17.5, 5.75, 41.75, 13.0, 0.793749988079071, 0.5665178298950195, 0.42743057012557983, 0.6177269220352173]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"mrxqNiKEBfxj","colab_type":"text"},"source":["# **meniscus**"]},{"cell_type":"code","metadata":{"id":"qvsefaZPBfDr","colab_type":"code","outputId":"a76e68a0-1fcf-46c7-c1bf-b7df6e6ec48c","executionInfo":{"status":"ok","timestamp":1591117867936,"user_tz":-120,"elapsed":8325,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["# load train, test,  valid data \n","label_type = \"meniscus\"\n","exam_view =\"axial\"\n","data_path = \"/content/gdrive/My Drive/Colab Notebooks/MRNet/dataset/MRNet-v1.0\"\n","p, l = partition(data_path)\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/train-meniscus.csv', newline='') as csvfile:\n","      data_train = list(csv.reader(csvfile))\n","x_train = np.array(data_train,dtype='float32')\n","x_train  = x_train[:,1:4]\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/test-meniscus.csv', newline='') as csvfile:\n","      data_test = list(csv.reader(csvfile))\n","x_test = np.array(data_test,dtype='float32')\n","x_test  = x_test[:,1:4]\n","\n","with open(f'/content/gdrive/My Drive/Colab Notebooks/MRNet/intermediate_dataset/valid-meniscus.csv', newline='') as csvfile:\n","      data_valid = list(csv.reader(csvfile))\n","x_valid = np.array(data_valid,dtype='float32')\n","x_valid  = x_valid[:,1:4]\n","\n","# load labels\n","ids_train = sorted(p['train'][exam_view]);\n","ids_test = sorted(p['test'][exam_view]);\n","ids_valid = sorted(p['valid'][exam_view]);\n","\n","arr = [] \n","for e in ids_train:\n","  arr.append(l[e][label_type]);\n","\n","y_train = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","arr = [] \n","for e in ids_test:\n","  arr.append(l[e][label_type]);\n","\n","y_test = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","arr = [] \n","for e in ids_valid:\n","  arr.append(l[e][label_type]);\n","  \n","y_valid = np.array(arr,dtype='float32').reshape(len(arr), 1);\n","\n","# class weight for skewed classes\n","pos = 0\n","for e in p['train'][exam_view]:\n","  if l[e][label_type] == 1:\n","    pos += 1\n","total = len(p['train'][exam_view])\n","neg = total - pos\n","class_weight = {0: 1, 1: neg/pos}\n","if neg < pos:\n","  class_weight = {0: pos/neg, 1: 1}\n","\n","\n","model,cbs = LR_model(0.001,label = \"meniscus\",modelName=\"inception\");\n","\n","model.load_weights('/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.120.hdf5');\n","model.fit(x=x_train,y=y_train, validation_data =[x_test,y_test] ,epochs=150, initial_epoch = 120,verbose=1, class_weight=class_weight,callbacks=[cbs[0]],shuffle=False, use_multiprocessing=True, workers=6)"],"execution_count":64,"outputs":[{"output_type":"stream","text":["Train on 1017 samples, validate on 113 samples\n","Epoch 121/150\n","1017/1017 [==============================] - 0s 320us/step - loss: 0.1194 - tp: 194.6562 - fp: 6.7812 - tn: 326.3438 - fn: 0.0000e+00 - accuracy: 0.9872 - precision: 0.9674 - recall: 1.0000 - auc: 1.0000 - val_loss: 0.7420 - val_tp: 380.2500 - val_fp: 35.5000 - val_tn: 670.0000 - val_fn: 7.5000 - val_accuracy: 0.9610 - val_precision: 0.9151 - val_recall: 0.9809 - val_auc: 0.9938\n","\n","Epoch 00121: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.121.hdf5\n","Epoch 122/150\n","1017/1017 [==============================] - 0s 148us/step - loss: 0.1171 - tp: 579.6562 - fp: 52.7812 - tn: 1013.3438 - fn: 12.0000 - accuracy: 0.9601 - precision: 0.9151 - recall: 0.9790 - auc: 0.9940 - val_loss: 0.7430 - val_tp: 764.2500 - val_fp: 81.5000 - val_tn: 1357.0000 - val_fn: 20.5000 - val_accuracy: 0.9542 - val_precision: 0.9038 - val_recall: 0.9739 - val_auc: 0.9923\n","\n","Epoch 00122: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.122.hdf5\n","Epoch 123/150\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.1149 - tp: 963.6562 - fp: 98.7812 - tn: 1700.3438 - fn: 25.0000 - accuracy: 0.9553 - precision: 0.9064 - recall: 0.9744 - auc: 0.9928 - val_loss: 0.7442 - val_tp: 1148.2500 - val_fp: 127.5000 - val_tn: 2044.0000 - val_fn: 33.5000 - val_accuracy: 0.9520 - val_precision: 0.9001 - val_recall: 0.9717 - val_auc: 0.9918\n","\n","Epoch 00123: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.123.hdf5\n","Epoch 124/150\n","1017/1017 [==============================] - 0s 117us/step - loss: 0.1127 - tp: 1347.6562 - fp: 144.7812 - tn: 2387.3438 - fn: 38.0000 - accuracy: 0.9532 - precision: 0.9027 - recall: 0.9724 - auc: 0.9923 - val_loss: 0.7455 - val_tp: 1532.2500 - val_fp: 173.5000 - val_tn: 2731.0000 - val_fn: 46.5000 - val_accuracy: 0.9509 - val_precision: 0.8983 - val_recall: 0.9706 - val_auc: 0.9916\n","\n","Epoch 00124: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.124.hdf5\n","Epoch 125/150\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.1107 - tp: 1731.6562 - fp: 190.7812 - tn: 3074.3438 - fn: 51.0000 - accuracy: 0.9520 - precision: 0.9006 - recall: 0.9713 - auc: 0.9920 - val_loss: 0.7468 - val_tp: 1916.2500 - val_fp: 219.5000 - val_tn: 3418.0000 - val_fn: 59.5000 - val_accuracy: 0.9503 - val_precision: 0.8972 - val_recall: 0.9699 - val_auc: 0.9914\n","\n","Epoch 00125: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.125.hdf5\n","Epoch 126/150\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.1087 - tp: 2115.6562 - fp: 236.7812 - tn: 3761.3438 - fn: 64.0000 - accuracy: 0.9512 - precision: 0.8992 - recall: 0.9706 - auc: 0.9918 - val_loss: 0.7481 - val_tp: 2300.2500 - val_fp: 265.5000 - val_tn: 4105.0000 - val_fn: 72.5000 - val_accuracy: 0.9499 - val_precision: 0.8965 - val_recall: 0.9695 - val_auc: 0.9913\n","\n","Epoch 00126: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.126.hdf5\n","Epoch 127/150\n","1017/1017 [==============================] - 0s 132us/step - loss: 0.1068 - tp: 2499.6562 - fp: 282.7812 - tn: 4448.3438 - fn: 77.0000 - accuracy: 0.9507 - precision: 0.8983 - recall: 0.9701 - auc: 0.9916 - val_loss: 0.7494 - val_tp: 2684.2500 - val_fp: 311.5000 - val_tn: 4792.0000 - val_fn: 85.5000 - val_accuracy: 0.9496 - val_precision: 0.8960 - val_recall: 0.9691 - val_auc: 0.9912\n","\n","Epoch 00127: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.127.hdf5\n","Epoch 128/150\n","1017/1017 [==============================] - 0s 138us/step - loss: 0.1049 - tp: 2883.6562 - fp: 328.7812 - tn: 5135.3438 - fn: 90.0000 - accuracy: 0.9503 - precision: 0.8976 - recall: 0.9697 - auc: 0.9915 - val_loss: 0.7507 - val_tp: 3068.2500 - val_fp: 357.5000 - val_tn: 5479.0000 - val_fn: 98.5000 - val_accuracy: 0.9494 - val_precision: 0.8957 - val_recall: 0.9689 - val_auc: 0.9911\n","\n","Epoch 00128: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.128.hdf5\n","Epoch 129/150\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.1031 - tp: 3267.6562 - fp: 374.7812 - tn: 5822.3438 - fn: 103.0000 - accuracy: 0.9500 - precision: 0.8971 - recall: 0.9694 - auc: 0.9914 - val_loss: 0.7521 - val_tp: 3452.2500 - val_fp: 403.5000 - val_tn: 6166.0000 - val_fn: 111.5000 - val_accuracy: 0.9492 - val_precision: 0.8954 - val_recall: 0.9687 - val_auc: 0.9910\n","\n","Epoch 00129: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.129.hdf5\n","Epoch 130/150\n","1017/1017 [==============================] - 0s 131us/step - loss: 0.1013 - tp: 3651.6562 - fp: 420.7812 - tn: 6509.3438 - fn: 116.0000 - accuracy: 0.9498 - precision: 0.8966 - recall: 0.9692 - auc: 0.9913 - val_loss: 0.7534 - val_tp: 3836.2500 - val_fp: 449.5000 - val_tn: 6853.0000 - val_fn: 124.5000 - val_accuracy: 0.9490 - val_precision: 0.8951 - val_recall: 0.9686 - val_auc: 0.9910\n","\n","Epoch 00130: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.130.hdf5\n","Epoch 131/150\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.0996 - tp: 4035.6562 - fp: 466.7812 - tn: 7196.3438 - fn: 129.0000 - accuracy: 0.9496 - precision: 0.8963 - recall: 0.9690 - auc: 0.9912 - val_loss: 0.7548 - val_tp: 4220.2500 - val_fp: 495.5000 - val_tn: 7540.0000 - val_fn: 137.5000 - val_accuracy: 0.9489 - val_precision: 0.8949 - val_recall: 0.9684 - val_auc: 0.9910\n","\n","Epoch 00131: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.131.hdf5\n","Epoch 132/150\n","1017/1017 [==============================] - 0s 138us/step - loss: 0.0979 - tp: 4419.6562 - fp: 512.7812 - tn: 7883.3438 - fn: 142.0000 - accuracy: 0.9494 - precision: 0.8960 - recall: 0.9689 - auc: 0.9912 - val_loss: 0.7561 - val_tp: 4604.2500 - val_fp: 541.5000 - val_tn: 8227.0000 - val_fn: 150.5000 - val_accuracy: 0.9488 - val_precision: 0.8948 - val_recall: 0.9683 - val_auc: 0.9909\n","\n","Epoch 00132: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.132.hdf5\n","Epoch 133/150\n","1017/1017 [==============================] - 0s 139us/step - loss: 0.0963 - tp: 4803.6562 - fp: 558.7812 - tn: 8570.3438 - fn: 155.0000 - accuracy: 0.9493 - precision: 0.8958 - recall: 0.9687 - auc: 0.9911 - val_loss: 0.7575 - val_tp: 4988.2500 - val_fp: 587.5000 - val_tn: 8914.0000 - val_fn: 163.5000 - val_accuracy: 0.9488 - val_precision: 0.8946 - val_recall: 0.9683 - val_auc: 0.9908\n","\n","Epoch 00133: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.133.hdf5\n","Epoch 134/150\n","1017/1017 [==============================] - 0s 127us/step - loss: 0.0947 - tp: 5187.6562 - fp: 604.7812 - tn: 9257.3438 - fn: 168.0000 - accuracy: 0.9492 - precision: 0.8956 - recall: 0.9686 - auc: 0.9910 - val_loss: 0.7588 - val_tp: 5372.2500 - val_fp: 633.5000 - val_tn: 9601.0000 - val_fn: 176.5000 - val_accuracy: 0.9487 - val_precision: 0.8945 - val_recall: 0.9682 - val_auc: 0.9908\n","\n","Epoch 00134: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.134.hdf5\n","Epoch 135/150\n","1017/1017 [==============================] - 0s 127us/step - loss: 0.0932 - tp: 5571.6562 - fp: 650.7812 - tn: 9944.3438 - fn: 181.0000 - accuracy: 0.9491 - precision: 0.8954 - recall: 0.9685 - auc: 0.9910 - val_loss: 0.7602 - val_tp: 5756.2500 - val_fp: 679.5000 - val_tn: 10288.0000 - val_fn: 189.5000 - val_accuracy: 0.9486 - val_precision: 0.8944 - val_recall: 0.9681 - val_auc: 0.9908\n","\n","Epoch 00135: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.135.hdf5\n","Epoch 136/150\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.0917 - tp: 5955.6562 - fp: 696.7812 - tn: 10631.3438 - fn: 194.0000 - accuracy: 0.9490 - precision: 0.8952 - recall: 0.9684 - auc: 0.9909 - val_loss: 0.7616 - val_tp: 6140.2500 - val_fp: 725.5000 - val_tn: 10975.0000 - val_fn: 202.5000 - val_accuracy: 0.9486 - val_precision: 0.8943 - val_recall: 0.9681 - val_auc: 0.9907\n","\n","Epoch 00136: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.136.hdf5\n","Epoch 137/150\n","1017/1017 [==============================] - 0s 135us/step - loss: 0.0902 - tp: 6339.6562 - fp: 741.9062 - tn: 11319.2188 - fn: 207.0000 - accuracy: 0.9490 - precision: 0.8952 - recall: 0.9684 - auc: 0.9908 - val_loss: 0.7629 - val_tp: 6524.2500 - val_fp: 770.5000 - val_tn: 11663.0000 - val_fn: 215.5000 - val_accuracy: 0.9486 - val_precision: 0.8944 - val_recall: 0.9680 - val_auc: 0.9906\n","\n","Epoch 00137: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.137.hdf5\n","Epoch 138/150\n","1017/1017 [==============================] - 0s 142us/step - loss: 0.0888 - tp: 6723.6562 - fp: 786.9062 - tn: 12007.2188 - fn: 220.0000 - accuracy: 0.9490 - precision: 0.8952 - recall: 0.9683 - auc: 0.9908 - val_loss: 0.7643 - val_tp: 6908.2500 - val_fp: 815.5000 - val_tn: 12351.0000 - val_fn: 228.5000 - val_accuracy: 0.9486 - val_precision: 0.8944 - val_recall: 0.9680 - val_auc: 0.9906\n","\n","Epoch 00138: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.138.hdf5\n","Epoch 139/150\n","1017/1017 [==============================] - 0s 118us/step - loss: 0.0874 - tp: 7107.6562 - fp: 831.9062 - tn: 12695.2188 - fn: 233.0000 - accuracy: 0.9490 - precision: 0.8952 - recall: 0.9683 - auc: 0.9908 - val_loss: 0.7656 - val_tp: 7292.2500 - val_fp: 860.5000 - val_tn: 13039.0000 - val_fn: 241.5000 - val_accuracy: 0.9486 - val_precision: 0.8945 - val_recall: 0.9679 - val_auc: 0.9906\n","\n","Epoch 00139: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.139.hdf5\n","Epoch 140/150\n","1017/1017 [==============================] - 0s 118us/step - loss: 0.0860 - tp: 7491.6562 - fp: 876.9062 - tn: 13383.2188 - fn: 246.0000 - accuracy: 0.9489 - precision: 0.8952 - recall: 0.9682 - auc: 0.9907 - val_loss: 0.7670 - val_tp: 7676.2500 - val_fp: 905.5000 - val_tn: 13727.0000 - val_fn: 254.5000 - val_accuracy: 0.9486 - val_precision: 0.8945 - val_recall: 0.9679 - val_auc: 0.9905\n","\n","Epoch 00140: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.140.hdf5\n","Epoch 141/150\n","1017/1017 [==============================] - 0s 140us/step - loss: 0.0847 - tp: 7875.6562 - fp: 921.9062 - tn: 14071.2188 - fn: 259.0000 - accuracy: 0.9489 - precision: 0.8952 - recall: 0.9682 - auc: 0.9907 - val_loss: 0.7683 - val_tp: 8060.2500 - val_fp: 950.5000 - val_tn: 14415.0000 - val_fn: 267.5000 - val_accuracy: 0.9486 - val_precision: 0.8945 - val_recall: 0.9679 - val_auc: 0.9905\n","\n","Epoch 00141: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.141.hdf5\n","Epoch 142/150\n","1017/1017 [==============================] - 0s 141us/step - loss: 0.0834 - tp: 8259.6562 - fp: 966.9062 - tn: 14759.2188 - fn: 272.0000 - accuracy: 0.9489 - precision: 0.8952 - recall: 0.9681 - auc: 0.9906 - val_loss: 0.7697 - val_tp: 8444.2500 - val_fp: 995.5000 - val_tn: 15103.0000 - val_fn: 280.5000 - val_accuracy: 0.9486 - val_precision: 0.8945 - val_recall: 0.9679 - val_auc: 0.9905\n","\n","Epoch 00142: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.142.hdf5\n","Epoch 143/150\n","1017/1017 [==============================] - 0s 118us/step - loss: 0.0822 - tp: 8643.6562 - fp: 1011.9062 - tn: 15447.2188 - fn: 285.0000 - accuracy: 0.9489 - precision: 0.8952 - recall: 0.9681 - auc: 0.9906 - val_loss: 0.7710 - val_tp: 8828.2500 - val_fp: 1040.5000 - val_tn: 15791.0000 - val_fn: 293.5000 - val_accuracy: 0.9486 - val_precision: 0.8946 - val_recall: 0.9678 - val_auc: 0.9904\n","\n","Epoch 00143: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.143.hdf5\n","Epoch 144/150\n","1017/1017 [==============================] - 0s 128us/step - loss: 0.0810 - tp: 9027.6562 - fp: 1056.9062 - tn: 16135.2188 - fn: 298.0000 - accuracy: 0.9489 - precision: 0.8952 - recall: 0.9680 - auc: 0.9905 - val_loss: 0.7723 - val_tp: 9212.2500 - val_fp: 1085.5000 - val_tn: 16479.0000 - val_fn: 306.5000 - val_accuracy: 0.9486 - val_precision: 0.8946 - val_recall: 0.9678 - val_auc: 0.9904\n","\n","Epoch 00144: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.144.hdf5\n","Epoch 145/150\n","1017/1017 [==============================] - 0s 129us/step - loss: 0.0798 - tp: 9411.6562 - fp: 1101.9062 - tn: 16823.2188 - fn: 311.0000 - accuracy: 0.9489 - precision: 0.8952 - recall: 0.9680 - auc: 0.9905 - val_loss: 0.7737 - val_tp: 9595.2500 - val_fp: 1130.5000 - val_tn: 17167.0000 - val_fn: 320.5000 - val_accuracy: 0.9486 - val_precision: 0.8946 - val_recall: 0.9677 - val_auc: 0.9903\n","\n","Epoch 00145: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.145.hdf5\n","Epoch 146/150\n","1017/1017 [==============================] - 0s 132us/step - loss: 0.0786 - tp: 9794.6562 - fp: 1146.9062 - tn: 17511.2188 - fn: 325.0000 - accuracy: 0.9488 - precision: 0.8952 - recall: 0.9679 - auc: 0.9904 - val_loss: 0.7750 - val_tp: 9978.2500 - val_fp: 1175.5000 - val_tn: 17855.0000 - val_fn: 334.5000 - val_accuracy: 0.9485 - val_precision: 0.8946 - val_recall: 0.9676 - val_auc: 0.9903\n","\n","Epoch 00146: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.146.hdf5\n","Epoch 147/150\n","1017/1017 [==============================] - 0s 134us/step - loss: 0.0775 - tp: 10177.6562 - fp: 1191.9062 - tn: 18199.2188 - fn: 339.0000 - accuracy: 0.9488 - precision: 0.8952 - recall: 0.9678 - auc: 0.9904 - val_loss: 0.7763 - val_tp: 10361.2500 - val_fp: 1220.5000 - val_tn: 18543.0000 - val_fn: 348.5000 - val_accuracy: 0.9485 - val_precision: 0.8946 - val_recall: 0.9675 - val_auc: 0.9903\n","\n","Epoch 00147: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.147.hdf5\n","Epoch 148/150\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.0763 - tp: 10560.6562 - fp: 1236.8125 - tn: 18887.3125 - fn: 353.0000 - accuracy: 0.9488 - precision: 0.8952 - recall: 0.9677 - auc: 0.9904 - val_loss: 0.7777 - val_tp: 10744.2500 - val_fp: 1264.5000 - val_tn: 19232.0000 - val_fn: 362.5000 - val_accuracy: 0.9485 - val_precision: 0.8947 - val_recall: 0.9674 - val_auc: 0.9902\n","\n","Epoch 00148: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.148.hdf5\n","Epoch 149/150\n","1017/1017 [==============================] - 0s 133us/step - loss: 0.0752 - tp: 10943.6562 - fp: 1280.8125 - tn: 19576.3125 - fn: 367.0000 - accuracy: 0.9488 - precision: 0.8952 - recall: 0.9675 - auc: 0.9903 - val_loss: 0.7790 - val_tp: 11127.2500 - val_fp: 1308.5000 - val_tn: 19921.0000 - val_fn: 376.5000 - val_accuracy: 0.9485 - val_precision: 0.8948 - val_recall: 0.9673 - val_auc: 0.9902\n","\n","Epoch 00149: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.149.hdf5\n","Epoch 150/150\n","1017/1017 [==============================] - 0s 127us/step - loss: 0.0742 - tp: 11326.6562 - fp: 1324.8125 - tn: 20265.3125 - fn: 381.0000 - accuracy: 0.9488 - precision: 0.8953 - recall: 0.9675 - auc: 0.9903 - val_loss: 0.7803 - val_tp: 11510.2500 - val_fp: 1352.5000 - val_tn: 20610.0000 - val_fn: 390.5000 - val_accuracy: 0.9485 - val_precision: 0.8949 - val_recall: 0.9672 - val_auc: 0.9901\n","\n","Epoch 00150: saving model to /content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.150.hdf5\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["<keras.callbacks.callbacks.History at 0x7f09c4c01f60>"]},"metadata":{"tags":[]},"execution_count":64}]},{"cell_type":"code","metadata":{"id":"Y2BdT7C1BUeM","colab_type":"code","outputId":"c4b685f2-1c1d-4999-f22b-a93f5f4f6e5c","executionInfo":{"status":"ok","timestamp":1591117895874,"user_tz":-120,"elapsed":1954,"user":{"displayName":"inception four","photoUrl":"","userId":"14769518731786345823"}},"colab":{"base_uri":"https://localhost:8080/","height":52}},"source":["model,cbs = LR_model(0,label = \"meniscus\",modelName=\"inception\");\n","model.load_weights('/content/gdrive/My Drive/Colab Notebooks/MRNet/training_inception_LR/meniscus/weights.150.hdf5');\n","metrics = model.evaluate(x=x_valid,y=y_valid,verbose=1);\n","print(metrics)"],"execution_count":68,"outputs":[{"output_type":"stream","text":["120/120 [==============================] - 0s 769us/step\n","[0.6233454823493958, 16.25, 14.75, 41.0, 6.0, 0.7588541507720947, 0.38496577739715576, 0.6057692170143127, 0.6184582710266113]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"3WuH1rtjBvba","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]}]}