automatic-ecg-diagnosis and ecg-age-prediction
About automatic-ecg-diagnosis
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.
About ecg-age-prediction
antonior92/ecg-age-prediction
Scripts and modules for training and testing neural network for age prediction from the ECG. Companion code to the paper "Deep neural network-estimated electrocardiographic age as a mortality predictor".
This project helps medical researchers and cardiologists predict a patient's biological age using electrocardiogram (ECG) data. It takes raw 12-lead ECG tracings as input and outputs a predicted age, which can then be used to assess health risks, such as mortality. The main users are researchers in cardiology or public health.
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