Artificial Intelligence in Sports Medicine: Diagnosis and Management

Dear Colleagues,

Artificial intelligence (AI) is accelerating clinical progress in sports medicine by improving diagnostic accuracy, streamlining decision-making, and personalizing athlete monitoring. This Special Issue highlights validated AI methodologies that enhance the early detection and management of conditions associated with athletic performance, health, and safety.

Submissions are invited on AI-enabled applications regarding the following topics:

• Sports cardiology and screening: automated ECG interpretation, arrhythmia and cardiomyopathy detection, AI-assisted echocardiography and CPET analytics, and prediction models for sudden cardiac death risk in athletes.
• Musculoskeletal diagnostics and recovery optimization: computer vision and multimodal algorithms for accurate detection of soft-tissue and bone pathology, prognosis of reinjury risk, and objective return-to-play assessment.
• Performance physiology and load regulation: sensor-based and wearable data analytics for quantifying neuromuscular function, cumulative training stress, biomechanical efficiency, and fatigue-related impairment.
• Biomarker and molecular profiling: integration of biochemical, hormonal, and multi-omics signatures to identify maladaptation, overtraining, RED-S, and performance-limiting physiological dysregulation.
• Validation and clinical governance: evidence-based evaluation of AI tools to confirm diagnostic accuracy, minimize error rates, ensure transparent decision-making, and clearly define clinician oversight when used in athlete care.

This Special Issue aims to advance safe, scientifically validated AI implementation that complements medical expertise and supports athlete well-being throughout the continuum of training, competition, and recovery.

Prof. Dr. Anca Ionescu
Guest Editor

Manuscript Submission Information

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