A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology

Experimental evaluation across varied athlete cohorts demonstrates superior performance in risk stratification accuracy, diagnostic plausibility, and model transparency compared to traditional screening algorithms. This multimodal framework not only advances the fidelity of cardiovascular screening in athletic populations but also establishes a scalable and principled foundation for integrating computational diagnostics with real-world cardiological assessment practices.