RESEARCH-PAPER:{
TITLE: "Multi-module Recurrent Convolutional Neural Network with Transformer Encoder for ECG Arrhythmia Classification",
CITE: "https://ieeexplore.ieee.org/abstract/document/9508527",
YEAR: 2021,
CONFERENCE: "IEEE EMBS",
AUTHORS: ["Duc Le^",
"Vidhiwar Singh Rathour^",
"Sang Truong",
"Quan Mai^,
Patel Brijesh;
Ngan Le"],
^: Equal Contribution}
DIRECTORY-TREE:{
data: "Directory: Datasets for training are stored here.",
utils: "Directory: Utility based files",
examples: {"Directory: github/awni/ecg/":[
"Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network"]},
models:{ "Directory: DNN Models": {
resnet_cnn.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, CNN, Word2Vec",
resnet_lstm_phy2017.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN",
resnet_lstm.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN",
resnet_w2v.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN, Word2Vec",
resnet_lstm_mitbih.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN, Word2Vec, Attention AYN"}},
ecg_cnn.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, CNN, Resnet",
ecg_w2v.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, Word2Vec, Resnet",
ecg_lstm.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN, LSTM",
ecg_phy2017.py:"Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN",
ecg_mitbih.py: "Python: Pytorch implememntation of Multimodal-ecg-classification, LSTM, CNN, Word2Vec, Attention AYN",
transform_data.ipynb: "Jupyter Notebook: Python implementation for Data Generation, and Preprocessing"}
HOW-TO-USE:{
Uno: "Make sure the required libraries (Torch, Panda, Tqdm, ... etc.,). are installed",
Dos: : "Use the examples directory to download and preprocess data.",
Tres: "Follow transform_data.ipyn to get data ready for training.",
Cuatro: "Run python ecg_###.py to train on training data, and validate on validation data",
Cinco: "By default results are saved in checkpoints directory"}
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