bbj-lab/protoecgnet
Case-based interpretable deep learning for ECG classification. This code implements ProtoECGNet from the following paper: "ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification." Sethi et al., MLHC 2025
This project helps medical researchers and cardiologists classify various heart conditions from electrocardiogram (ECG) data. By inputting raw ECG signals, it provides a classification of heart diseases, along with clear, case-based explanations that show which specific ECG patterns or 'prototypes' led to a particular diagnosis. This allows for a deeper understanding of the model's reasoning, making it useful for both research and clinical interpretation.
No commits in the last 6 months.
Use this if you are a medical researcher or clinician needing to classify multiple heart conditions from ECGs and require an interpretable system that explains its diagnostic reasoning with real-world examples.
Not ideal if you are a practitioner looking for a black-box diagnostic tool without needing to understand the underlying reasoning, or if you don't have access to or expertise in working with raw ECG datasets and Python development environments.
Stars
28
Forks
9
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 08, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/bbj-lab/protoecgnet"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DeepPSP/torch_ecg
Deep learning ECG models implemented using PyTorch
im-ethz/flirt
Are you ready to FLIRT with your wearable data?
Edoar-do/HuBERT-ECG
A self-supervised foundation ECG model for broad and scalable cardiac applications
bowang-lab/ecg-fm
An electrocardiogram analysis foundation model.
antonior92/automatic-ecg-diagnosis
Scripts and modules for training and testing neural network for ECG automatic classification....