Orod Razeghi, Ridhima Kapoor, Mahmood I Alhusseini, Muhammad Fazal, Siyi Tang, Caroline H Roney, Albert J Rogers, Anson Lee, Paul J Wang, Paul Clopton, Daniel L Rubin, Sanjiv M Narayan, Steven Niederer, Tina Baykaner
BACKGROUND: Structural changes in the left atrium (LA) modestly predict outcomes in patients undergoing catheter ablation for atrial fibrillation (AF). Machine learning (ML) is a promising approach to personalize AF management strategies and improve predictive risk models after catheter ablation by integrating atrial geometry from cardiac computed tomography (CT) scans and patient-specific clinical data. We hypothesized that ML approaches based on a patient's specific data can identify responders to AF ablation...
March 19, 2023: Journal of Cardiovascular Electrophysiology