Operator Learning Predicts Cardiac Activation And Repolarization
Ziarelli et al. (published January 27, 2026) apply Fourier Neural Operators (FNO) and Kernel Operator Learning (KOL) to map applied electrical stimuli to cardiac activation and repolarization times. They evaluate models on synthetic 2D and 3D domains and a realistic left-ventricle geometry, reporting high accuracy and orders-of-magnitude speedups versus Monodomain solvers, enabling fast surrogate simulations for clinical use.
Scoring Rationale
High novelty and strong usability from peer-reviewed methods; scope limited to simulated cases and a single left-ventricle geometry.
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