ChristophReich1996/ECG_Classification
Official and maintained implementation of the paper "Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in Medical Machine Learning" (ECG-DualNet) [Physiological Measurement 2022, EMBC 2023].
This project offers a method for automatically detecting Atrial Fibrillation (AFib) from electrocardiogram (ECG) data. It takes raw ECG signals as input and classifies them to identify the presence of AFib. This tool is designed for medical researchers, cardiologists, and healthcare professionals who analyze heart rhythm data.
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Use this if you need to classify ECG recordings to detect Atrial Fibrillation using deep learning models.
Not ideal if you are looking for a certified medical device or a solution for real-time patient monitoring without further integration and validation.
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Language
Python
License
MIT
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Last pushed
Jul 18, 2023
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