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Artificial Intelligence‐Enhanced Electrocardiography for Predicting Paroxysmal Atrial Fibrillation From Sinus Rhythm: Impact of Data Integration Across Institutions and Devices

ABSTRACT Background Artificial intelligence (AI)‐enhanced electrocardiography (ECG) has been developed to detect paroxysmal atrial fibrillation (AF) from sinus rhythm ECGs (SR‐ECGs). For broader applicability, model development across institutions and ECG systems is essential. Methods We developed a...

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Principais autores: Shinya Suzuki, Mari Amino, Nobumoto Moriai, Yoshifumi Sumioka, Akira Hyodo, Keiichi Satoh, Tsuneo Takayanagi, Takuya Umemoto, Yota Sekiguchi, Naomi Hirota, Atsuhiko Yagishita, Yuji Ikari, Taira Nakayama, Yoichi Ohnuki, Eiichiro Nagata, Jun Motogi, Takeshi Yamashita, Koichiro Yoshioka
Format: Artigo
Sprog:Inglês
Udgivet: Wiley 2026-03-01
Serier:Annals of Noninvasive Electrocardiology
Fag:
artificial intelligence
atrial fibrillation
electrocardiography
Online adgang:https://doi.org/10.1111/anec.70159
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