Can Artificial Intelligence Enhance Syncope Management?
Giselle M. Statz, Aron Z. Evans, Samuel L. Johnston, Mehul Adhaduk, Avinash Mudireddy, Milan Sonka, Sangil Lee, Ercole John Barsotti, Fabrizio Ricci, Franca Dipaola, Madeleine Johansson, Robert S. Sheldon, Venkatesh Thiruganasambandamoorthy, Rose Anne Kenny, Tyler Bullis, Deepak Kumar Pasupula, Jon Van Heukelom, Milena A. Gebska, Brian Olshansky
Abstract
Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative statement, from a multidisciplinary group of clinicians, investigators, and scientists, focuses on the potential role of AI in syncope management with a goal to inspire creation of AI-derived clinical decision support tools that may improve patient outcomes, streamline diagnostics, and reduce health-care costs.