Robert Herman, Anthony Demolder, Boris Vavrik, Michal Martonak, Vladimir Boza, Viera Kresnakova, Andrej Iring, Timotej Palus, Jakub Bahyl, Olivier Nelis, Monika Beles, Davide Fabbricatore, Leor Perl, Jozef Bartunek, Robert Hatala
BACKGROUND: The electrocardiogram (ECG) is one of the most accessible and comprehensive diagnostic tools used to assess cardiac patients at the first point of contact. Despite advances in computerized interpretation of the electrocardiogram (CIE), its accuracy remains inferior to physicians. This study evaluated the diagnostic performance of an artificial intelligence (AI)-powered ECG system and compared its performance to current state-of-the-art CIE. METHODS: An AI-powered system consisting of 6 deep neural networks (DNN) was trained on standard 12‑lead ECGs to detect 20 essential diagnostic patterns (grouped into 6 categories: rhythm, acute coronary syndrome (ACS), conduction abnormalities, ectopy, chamber enlargement and axis)...
December 23, 2023: Journal of Electrocardiology