Chest X-Ray Medical Diagnosis with Deep Learning - ① Import Packages and Function

Chest X-Ray Medical Diagnosis with Deep Learning - ① Import Packages and Function

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BioinformaticsAndMe

 

 

 

Chest X-Ray Medical Diagnosis with Deep Learning

     ① Import Packages and Function
     ② Load the Datasets
     ③ Model Development
     ④ Training
    ⑤ Prediction and Evaluation 

 

 

 

 

Chest X-Ray Medical Diagnosis with Deep Learning 시작

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: Keras를 사용하여 흉부 X-ray classifier 딥러닝 모델을 생성하여, 의료 영상 진단에 사용해보는 학습 과정

: 모든 분석 과정은 google colab에서 수행되었음

: 실제 X-ray 데이터 전처리부터 모델 평가까지 아래의 과정을 수행

• Data preparation
  • Visualizing data
  • Preventing data leakage
• Model Development
  • Addressing class imbalance
  • Leveraging pre-trained models using transfer learning
• Evaluation
  • AUC and ROC curves

 

 

 

 

① Import Packages and Function

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: numpy, pandas - 데이터 전처리, 가공

: matplotlib.pyplot, seaborn - 결과 플롯팅으로 시각화

: util - 로컬로 정의된 유틸리티 기능 제공

: keras - 딥러닝 모델 구축

util.py

0.00MB

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

from keras.preprocessing.image import ImageDataGenerator
from keras.applications.densenet import DenseNet121
from keras.layers import Dense, GlobalAveragePooling2D
from keras.models import Model
from tensorflow.compat.v1.keras import backend as K

from keras.models import load_model

# 아래 코드를 실행하여 util.py을 업로드
from google.colab import files
src = list(files.upload().values())[0]
open('util.py','wb').write(src)
import util

 

 

 

다음 분석

Chest X-Ray Medical Diagnosis with Deep Learning

    ② Load the Datasets

 

 

 

#Reference

1) www.coursera.org/learn/ai-for-medical-diagnosis

 

 

 

 

Chest X-Ray Medical Diagnosis with Deep Learning - ① Import Packages and Function

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