Artificial Intelligence in Sports Medicine: Diagnosis and Management
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: 15 July 2026 | Viewed by 4
Special Issue Editor
Interests: sports medicine; sports cardiology; exercise physiology; athlete health; performance optimization; cardiovascular safety; artificial intelligence; wearable monitoring; biomarker profiling; sports nutrition; recovery science; evidence-based protocols for prevention, diagnosis, and rehabilitation in elite athletes
Special Issue Information
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
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sports medicine
- sports cardiology
- exercise physiology
- artificial intelligence
- athlete health
- performance monitoring
- biomarkers
- sports nutrition
- injury prevention
- rehabilitation
- wearable technology
- clinical validation
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