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.
Stroke prevention in atrial fibrillation: Looking forward
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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.