Neal Yuan, Nathan R Stein, Grant Duffy, Roopinder K Sandhu, Sumeet S Chugh, Peng-Sheng Chen, Carine Rosenberg, Christine M Albert, Susan Cheng, Robert J Siegel, David Ouyang
Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0...
April 13, 2024: NPJ Digital Medicine