ReviewFrontiers in public health2026
Building smarter surveillance: a framework for artificial intelligence-enabled monitoring of overuse injuries in youth sports.
Review in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors.
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Abstract
Early sport specialization (ESS), defined as intensive, year-round training in a single sport at the exclusion of others, has become increasingly prevalent among youth athletes. This trend has coincided with a rise in overuse injuries, and premature attrition. Concurrently, advances in wearable sensors and artificial intelligence (AI) enable real-time quantification of training load, biomechanical deviations, and recovery. However, a translational gap remains: existing AI surveillance models are predominantly validated in elite adult male cohorts, leaving youth athletes underserved. To address this gap, we propose a translational four-pillar framework for ESS-aware AI injury monitoring in youth sport. Bridging technological capabilities with developmental physiology through structured AI surveillance provides a structured risk-monitoring roadmap with the potential to inform preventative strategies, optimize physical readiness, and support long-term musculoskeletal health in youth athletes.
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