Beatwise ECG Classification for the Detection of Atrial Fibrillation with Deep Learning
Author:
Affiliation:
1. University of Auckland,Auckland Bioengineering Institute,New Zealand
2. Waitemata District Health Board,Auckland,New Zealand
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10339936/10339939/10341199.pdf?arnumber=10341199
Reference14 articles.
1. The Infant Mortality Rate, Life Expectancy at Birth, and a Linear Index of Mortality as Measures of General Health Status
2. AF Classification from a Short Single Lead ECG Recording: the PhysioNet computing in Cardiology Challenge 2017;Gari;Computing in Cardiology.,2017
3. Errors in the computerized electrocardiogram interpretation of cardiac rhythm
4. Robust ECG Signal Classification for the Detection of Atrial Fibrillation Using Novel Neural Networks
5. ENCASE: an ENsemble ClASsifiEr for ECG Classification Using Expert Features and Deep Neural Networks
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