seorim0/ResUNet-LC
2D residual U-Net (ResUNet) and a lead combiner (LC) for 12-lead ECG Abnormality Classification
This project helps medical researchers and cardiologists automatically classify various abnormalities from 12-lead ECG recordings. It takes raw ECG data as input and outputs a multi-label classification of potential cardiac conditions. This tool is designed for medical professionals or researchers working with large datasets of electrocardiograms.
No commits in the last 6 months.
Use this if you need to automate the detection of multiple cardiac abnormalities from 12-lead ECG signals with high accuracy.
Not ideal if you are looking for a simple, out-of-the-box diagnostic tool for clinical use without a development setup.
Stars
15
Forks
1
Language
Python
License
MIT
Category
Last pushed
Jan 04, 2024
Commits (30d)
0
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