医学
疾病
心脏病
心脏病学
深度学习
内科学
重症监护医学
儿科
人工智能
计算机科学
作者
Joshua Mayourian,Amr El‐Bokl,Platon Lukyanenko,William La Cava,Tal Geva,Anne Marie Valente,John K. Triedman,Sunil J. Ghelani
标识
DOI:10.1093/eurheartj/ehae651
摘要
Robust and convenient risk stratification of patients with paediatric and adult congenital heart disease (CHD) is lacking. This study aims to address this gap with an artificial intelligence-enhanced electrocardiogram (ECG) tool across the lifespan of a large, diverse cohort with CHD.
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