Conference
Detecting Cardiac Abnormalities with Multi-Lead ECG Signals: A Modular Network Approach
Abstract
Globally, heart disease has been the leading cause of death for more than two decades. There is a need to develop intelligent architectures to handle a variety of real life clinical scenarios when a 12-lead ECG is not a viable option. We propose a method using wide and deep CNN architectures to classify cardiac abnormalities from 12, 6, 4, 3, and 2 leads ECGs. These five networks were created for the PhysioNet/CinC Challenge 2021, by the …
Authors
Clark R; Heydarian M; Siddiqui K; Rashidiani S; Khan A; Doyle TE
Volume
48
Pagination
pp. 1-4
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
January 15, 2021
DOI
10.23919/cinc53138.2021.9662677
Name of conference
2021 Computing in Cardiology (CinC)