ReviewBrazilian journal of physical therapy
Artificial intelligence and Machine Learning approaches in sports: Concepts, applications, challenges, and future perspectives.
Review in Brazilian journal of physical therapy. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Role of Machine Learning in Talent Identification for Team Sports: A Systematic Review.Journal of sports science & medicine · 2026Pooled it
- Machine learning-based personalized training models for optimizing marathon performance through pyramidal and polarized training intensity distributions.Scientific reports · 2025Trial
- Development of an individualized prediction model for dynamic adaptations in performance and immune function associated with dietary patterns in endurance athletes using machine learning.Journal of the International Society of Sports Nutrition · 2026Observational
- Article
- Review
- The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.Journal of evaluation in clinical practice · 2026Review
- Exercise and Sports Metabolomics: Analytical Platforms, Metabolite Annotation, Pathway-Level Interpretation, and Biomarker-Panel Readiness.Metabolites · 2026Review
- Data-Driven Reduction of External Load Variables in Indoor Team Sports Using Local Positioning System.Journal of functional morphology and kinesiology · 2026Article
- Analysis of decision support system of basketball sports competition based on machine learning and IoT.Scientific reports · 2026Article
- Machine Learning-Based Classification of Alertness Levels in Elite Shooting Athletes Using Heart Rate Variability.Journal of sports science & medicine · 2026Article
- Can Locomotor Performance Predict the Final Result of a Football Match? A Machine Learning Approach.Sensors (Basel, Switzerland) · 2026Article
- Machine Learning-Based Prediction of Performance Gaps in Rowing and Identification of Key Training Monitoring Indicators.Sensors (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Sports Medicine: A Decision-Centered Framework for the Future Sports Physician.Diagnostics (Basel, Switzerland) · 2026Review
- Advances in flexible wearable pressure/strain sensors for motion monitoring in orthopaedic sports medicine.Journal of orthopaedic translation · 2026Review
- [Progress and application of machine learning in sports injury research].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Review
- When more is not always better: exercise dose and children's cognitive development from an interpretable machine learning perspective.Frontiers in psychiatry · 2026Article
- Machine learning prediction of ACL loading during the wide lunge: a multifactorial coupling analysis based on kinematic and electromyographic signals.Frontiers in bioengineering and biotechnology · 2026Article
- Review
- Leveraging wearables to safeguard workers in a hotter climate.Frontiers in public health · 2026Article
- Artificial intelligence for university physical education: a data-knowledge synergy digital-intelligent sports platform.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe development and application of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare have gained attention as a promising and powerful resource to change the landscape of healthcare. The potential of these technologies for injury prediction, performance analysis, personalized training, and treatment comes with challenges related to the complexity of sports dynamics and the multidimensional aspects of athletic performance.
objectivesWe aimed to present the current state of AI and ML applications in sports science, specifically in the areas of injury prediction, performance enhancement, and rehabilitation. We also examine the challenges of incorporating AI and ML into sports and suggest directions for future research.
methodWe conducted a comprehensive literature review, focusing on publications related to AI and ML applications in sports. This review encompassed studies on injury prediction, performance analysis, and personalized training, emphasizing the AI and ML models applied in sports.
resultsThe findings highlight significant advancements in injury prediction accuracy, performance analysis precision, and the customization of training programs through AI and ML. However, future studies need to address challenges such as ethical considerations, data quality, interpretability of ML models, and the integration of complex data.
conclusionAI and ML may be useful for the prevention, detection, diagnosis, and treatment of health conditions. In this Masterclass paper, we introduce AI and ML concepts, outline recent breakthroughs in AI technologies and their applications, identify the challenges for further progress of AI systems, and discuss ethical issues, clinical and research opportunities, and future perspectives.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.