A graph recurrent network reconstructs whole-atria atrial fibrillation dynamics from 10% catheter coverage, with 2.1x lower error and 11x better phase singularity detection than weak baselines, and shows promise on three real clinical cases.
Lifetime risk of atrial fibrillation by race and socioeconomic status: ARIC study (Atherosclerosis Risk in Communities)
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Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements
A graph recurrent network reconstructs whole-atria atrial fibrillation dynamics from 10% catheter coverage, with 2.1x lower error and 11x better phase singularity detection than weak baselines, and shows promise on three real clinical cases.