Identifying Mitral Valve Prolapse at Risk for Arrhythmias and Fibrosis From Electrocardiograms Using Deep Learning

Geoffrey H. Tison,Sean Abreau,Joshua Barrios,Lisa J. Lim,Michelle Yang,Valentina Crudo,Dipan J. Shah,Thuy Nguyen,Gene Hu,Shalini Dixit,Gregory Nah, Farzin Arya,Dwight Bibby,Yoojin Lee,Francesca N. Delling

JACC. Advances（2023）

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摘要

CNN-analyzed 12-lead ECGs can detect MVP at risk for ventricular arrhythmias, death and/or fibrosis and can identify novel ECG correlates of arrhythmic risk. ECG-based CNNs may help select those MVP patients requiring closer follow-up and/or a CMR.

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关键词

artificial intelligence,computers,echocardiography,valvular heart disease

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