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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 - April 29, 2022 Category: Cardiology Authors: Yang Zhou, Yu Chen, Deyun Zhang, Shijia Geng, Guodong Wei, Ying Tian, Shenda Hong, XINGPENG LIU Source Type: research

I left my smartphone at home and can’t tell if I’m in atrial fibrillation
The enormous impact of atrial fibrillation (AF) on human suffering, health-care utilization, and physician resources is clear to the readers of HeartRhythm. Recent publications have developed 3 alarming trends: (1) the incidence of AF is increasing, perhaps fueled by the obesity epidemic; (2) our ability to treat AF is not improving, at least as assessed by age-adjusted mortality rates postdiagnosis; and (3) health-care costs for treatment of AF are growing exponentially. In reaction to these depressing facts, the tendency to want to learn more about our enemy is only natural. Improvements in bioengineering technology and ...
Source: Heart Rhythm - January 28, 2013 Category: Cardiology Authors: David J. Callans Tags: Editorial Commentary Source Type: research