Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation–Related Stroke
Atrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. Deep neural networks were trained to predict new-onset AF (within 1 year) in patients without a history of AF. We identified patients at risk for AF-related stroke among those predicted to be high risk by the model.

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