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

ABSTRACT:

Introduction

The increasing complexity of athlete cardiovascular risk profiles, coupled with evolving demands in pre-participation screening, necessitates robust, interpretable, and physiologically grounded assessment tools. Current approaches to cardiovascular screening, typically reliant on binary ECG interpretations or risk scores, often fall short in accurately differentiating benign athletic heart adaptations from early-stage pathological conditions, particularly across diverse athletic populations. These conventional systems are limited by their inability to capture multi-modal clinical inputs, susceptibility to diagnostic ambiguity, and lack of structured integration between exertional physiology and latent cardiovascular risk.

Methods

To address these challenges, we

SUBMITTER: Guo M 

PROVIDER: S-EPMC12702950 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature