Po-661-03 use of a deep learning algorithm to predict paroxysmal atrial fibrillation based on printed electrocardiographic records acquired during sinus rhythm
Atrial fibrillation (AF) is a common type of sustained arrhythmia worldwide. Asymptomatic AF, which occurs frequently, is associated with an increased incidence of ischemic stroke, heart failure, and mortality. A large number of patients with paroxysmal atrial fibrillation (PAF) remain undiagnosed due to the absence of electrocardiographic evidence of AF (AF-ECGs). If PAF could be predicted, targeted screening could improve early detection and treatment of this condition.
Source: Heart Rhythm - Category: Cardiology Authors: Yang Zhou, Yu Chen, Deyun Zhang, Shijia Geng, Guodong Wei, Ying Tian, Shenda Hong, XINGPENG LIU Source Type: research
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