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Po-04-151 a new sequential artificial intelligence algorithm for predicting atrial fibrillation using serial 12-lead electrocardiograms
Because the early stage of atrial fibrillation (AF) is difficult to detect, a significant number of patients are exposed to the risk of stroke without forewarning. Artificial intelligence (AI) algorithms using 12-lead electrocardiograms (ECGs) are being developed to detect AF early.
Source: Heart Rhythm - May 1, 2023 Category: Cardiology Authors: Jihoon Choi, Kyoung-Min Park Source Type: research

Dh-452784-2 identifying atrial fibrillation with sinus rhythm electrocardiogram using artificial intelligence in embolic stroke with undetermined source
Previous studies have demonstrated acceptable ranges of accuracy of artificial intelligence (AI) algorithms for identifying patients with paroxysmal atrial fibrillation (AF) based on their sinus rhythm electrocardiograms (ECGs). However, none of them has been validated in patients with embolic stroke with undetermined source (ESUS) in which thorough AF screening is required.
Source: Heart Rhythm - May 1, 2023 Category: Cardiology Authors: Ji Hyun Lee, Youngjin Cho, Joonghee Kim Source Type: research