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ChristophReich1996 / ECG_Classification

Official and maintained implementation of the paper "Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in Medical Machine Learning" (ECG-DualNet) [Physiological Measurement 2022, EMBC 2023].
https://iopscience.iop.org/article/10.1088/1361-6579/ac7840
MIT License
58 stars 9 forks source link

Compatibility with other systems #1

Closed ChristophReich1996 closed 3 years ago

ChristophReich1996 commented 3 years ago

Hey @MauriceRohr, could you please try to execute the code to make sure the code is runnable on your system. If any problems occur please let me know! The steps to install all dependencies are stated in the README.

You can simply run the train.py file with the smallest model for a single epoch by:

python -W ignore train.py --cuda_devices "0" --epochs 1 --batch_size 2 --dataset_path "data/training2017/" --network_config "ECGCNN_S"

The dataset path and the CUDA device might change for your system.

Cheers Christoph

ChristophReich1996 commented 3 years ago

@MauriceRohr requirements and dependencies should be fixed now. Thanks for the feedback!