konspatl/vae_scan
A deep learning library for XAI-ECG analysis
This framework helps clinical researchers and cardiologists analyze electrocardiogram (ECG) data using AI models. It takes raw ECG recordings and associated clinical factors as input to identify clear, understandable links between specific ECG features and patient conditions. The output provides explanations for AI predictions in terms a medical professional can interpret, enhancing trust in AI-driven diagnoses.
Use this if you need to understand *why* an AI model is making a particular prediction about ECG data, rather than just getting a 'yes' or 'no' answer.
Not ideal if you are looking for a pre-built diagnostic tool for immediate clinical use, as this is a framework for research and model development.
Stars
7
Forks
2
Language
Python
License
BSD-3-Clause
Category
Last pushed
Dec 08, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/konspatl/vae_scan"
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....