AI-driven wearable technologies for brain tumor risk assessment among professional athletes: a systematic review

Abstract

Introduction: the study addressed the emerging role of artificial intelligence combined with wearable technologies in the assessment of brain tumor risk among professional athletes. the importance of early detection and continuous monitoring was highlighted. Objective: the purpose of this study was to systematically review recent advances in wearable systems enhanced by artificial intelligence and to critically evaluate their applicability, effectiveness, and potential benefits for neurological risk assessment in professional athletes, with emphasis on early detection, monitoring, and preventive strategies. Methodology: a systematic review methodology was employed, analyzing recent studies on wearable biosensors, physiological monitoring techniques, and artificial intelligence algorithms. collected data were evaluated and synthesized comparatively to identify patterns, assess applicability, and highlight advancements in neurological risk assessment. Results: the study demonstrated that wearable devices integrated with artificial intelligence enabled reliable detection of early neurological abnormalities, effective monitoring of concussion-related risks, and comprehensive assessment of fatigue, recovery, and stress-related biomarkers in professional athletes, enhancing overall neurological health management. Discussion: the findings confirmed that AI-based wearables aligned with previous evidence in medical diagnostics, while also extending applications to sports medicine. the integration of multimodal sensing and real-time analytics was emphasized. Conclusions: AI-driven wearable technologies offer a pathway toward proactive, personalized risk assessment in athletes, with potential to enhance health, safety, and performance.

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