antonior92/automatic-ecg-diagnosis
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
This project provides tools to automatically classify 12-lead electrocardiogram (ECG) tracings to help diagnose heart conditions. It takes raw ECG signal data as input and outputs the probabilities of six common cardiac abnormalities, such as atrial fibrillation or different types of heart blocks. It's intended for medical researchers and practitioners who analyze ECGs and want to leverage deep learning for automated diagnostics.
437 stars. No commits in the last 6 months.
Use this if you need to automatically identify common cardiac abnormalities from 12-lead ECG signals using a pre-trained deep neural network.
Not ideal if you are looking for a plug-and-play clinical diagnostic tool or if you need to detect conditions outside of the six specified abnormalities.
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437
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137
Language
Python
License
MIT
Category
Last pushed
Mar 25, 2023
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