A systematic review of explainable artificial intelligence and cardiac electrophysiological models addressing sports-related sudden cardiac death and arrest in adolescents and young adults.
Vanegas Müller E., Srikijkasemwat N., Gan A., Raman B., Harford M., He L., Banerjee A., Gehmlich K., Leeson P., Villarroel M.
Sudden Cardiac Death (SCD) is a fatal event occurring within one hour of a witnessed or 24 hours of an unwitnessed Sudden Cardiac Arrest (SCA), being the leading medical cause of death among adolescent and young adult athletes. We examined the epidemiology of sports-related SCD (SrSCD) and SCA (SrSCA) incidence in adolescents and young adults, explainable Artificial Intelligence (xAI) applied to life-threatening arrhythmias, and cardiac electrophysiological models. We systematically searched peer-reviewed studies from eight databases between 2013-2025 (PROSPERO: CRD42024565960), using PROBAST for bias assessment. From 9574 studies, we included 84 (incidence: 16, xAI: 30, modelling: 38). SrSCD incidence ranged from 0.1 to 0.6 per 100,000 participants per year. Gradient-weighted Class Activation Mapping dominated as xAI technique. Cardiac electrophysiological models predominantly focused on cellular and tissue-level electrophysiology. We advocate for standardised SrSCD/SrSCA definitions and integration of epidemiological risk factors with xAI and cardiac modelling frameworks to advance athlete-specific risk stratification.