This is the code for the paper "A Multi-View Multi-Scale Neural Network for Multi-Label ECG Classification"
- python>=3.7
- pytorch>=1.7.0
- torchvision>=0.8.1
- numpy>=1.19.5
- tqdm>=4.62.0
- scipy>=1.5.4
- wfdb>=3.2.0
- scikit-learn>=0.24.2
There is a configuration file "config.py", where one can edit both the training and test options.
After setting the configuration, to start training, simply run
python main_train.py
Since MiniRocket's training strategy is slightly different from the others, to start training in MiniRocket, run
python minirocket_train.py
The multi-view network trained in the first stage is used to train the single-view network, run
python main_distillation.py
PTB-XL dataset can be downloaded from PTB-XL, a large publicly available electrocardiography dataset v1.0.1 (physionet.org).
CPSC2018 dataset can be downloaded from The China Physiological Signal Challenge 2018 (icbeb.org)
HFHC dataset can be downloaded from https://tianchi.aliyun.com/competition/entrance/231754/information
If you find this idea useful in your research, please consider citing:
@article{
title={A Multi-View Multi-Scale Neural Network for Multi-Label ECG Classification},
}