nakamotoo / ecg-pytorch-sample

A PyTorch implementation for training deep learning models for 12-lead ECGs (2D-CNN, 1D-CNN, Transformer)

This is a PyTorch implementation for training deep learning models for 12-lead ECGs (2D-CNN, 1D-CNN, Transformer)

Step1: Placing the raw data.

Place the raw csv files of ECG under data/ecg．

Step2: Generate FileList.csv

Next, we should split the data into train/valid/test dataset and generate a FileList．
Place the csv for annotated labels under data/Labels，
If you run data/FileList_Maker.ipynb , a file named FileList_{outcome}.csv will be generated under data/FileLists

Step3: Training

Run ./run.sh to train the models!

Else:

You can add various models to ecg/models
train.py : training code for CNN models.
train_tf.py : training code for Transformer models (with saving the attention maps at the same time).

生データの配置

まずは生のecgデータを配置する必要があります． data/ecg配下にcsvファイルをすべて入れます．

FileList.csv の作成

続いて， train/valid/test の FileList を作成します．data/Labelsにアノテーションしたcsvファイルを配置し， data/FileList_Maker.ipynb を実行すると，data/FileLists 配下に FileList_{outcome}.csv が保存されます

学習`

学習ようのpythonコードは，CNNモデルはrun.py, Transfomerモデルはrun_tf.pyです．run.sh, run_tf.shはそれぞれを実行するシェルスクリプトで，該当するパラメータを指定して，./run.shで学習が開始します．

ecg-pytorch-sample's Issues

dataset

Your work is excellent. Do you have any datasets you can recommend or share？