DeepPSP/torch_ecg
Deep learning ECG models implemented using PyTorch
This project helps medical researchers and data scientists working with Electrocardiogram (ECG) data. It streamlines the process of preparing raw ECG signals for analysis, allowing you to easily clean, augment, and manage your data. You input raw ECG recordings, and it outputs processed, standardized ECG signals ready for deep learning models, enabling more robust research into cardiac conditions.
254 stars. Available on PyPI.
Use this if you are a researcher or data scientist building deep learning models for ECG analysis and need a robust framework for data preprocessing and management.
Not ideal if you are looking for a clinical diagnostic tool or a ready-to-use application for interpreting ECGs without needing to build custom deep learning models.
Stars
254
Forks
31
Language
Python
License
MIT
Category
Last pushed
Mar 19, 2026
Commits (30d)
0
Dependencies
26
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