AI Medical Compendium Journal:
Journal of sports sciences

Showing 1 to 10 of 33 articles

Enhanced personalized prediction of baseball-related upper extremity injuries through novel features and explainable artificial intelligence.

Journal of sports sciences
Upper extremity injuries in baseball players demand advanced prevention. Our study analyzed clinical features using machine learning techniques to provide precise and individualized injury risk assessment and prediction. We recruited 98 baseball play...

Subjective recovery in professional soccer players: A machine learning and mediation approach.

Journal of sports sciences
Coaches often ask players to judge their recovery status (subjective recovery). We aimed to explore potential determinants of subjective recovery in 101 male professional soccer players of 4 Italian Serie C teams and to further investigate whether th...

Finding the needle in the haystack of isokinetic knee data: Random Forest modelling improves information about ACLR-related deficiencies.

Journal of sports sciences
The difficulties of rehabilitation after anterior cruciate ligament (ACL) injuries, subsequent return-to-sport (RTS) let alone achieving pre-injury performance, are well known. Isokinetic testing is often used to assess strength capacities during tha...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

Journal of sports sciences
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...

Early specialization in formative basketball: A machine learning analysis of shooting patterns in U14 and professional players.

Journal of sports sciences
Growing evidence supports that early sport specialization in children and adolescents may compromise long-term athlete development and high-performance acquisition. This study aimed to determine the presence of specialised shooting roles in formative...

What explains adolescents' physical activity and sports participation during the COVID-19 pandemic? - an interpretable machine learning approach.

Journal of sports sciences
Adolescents' physical activity (PA) and sports participation declined due to the COVID-19 pandemic. This study aimed to determine the critical socio-ecological factors for PA and sports participation using a machine learning approach. We did a cross-...

Artificial intelligence applications in the football codes: A systematic review.

Journal of sports sciences
Artificial Intelligence (AI) is increasingly being adopted across many domains such as transport, healthcare, defence and sport, with football codes no exception. Though there is a range of potential benefits of AI, concern has also been expressed re...

Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

Journal of sports sciences
The purpose of this study was to test whether a machine learning model can accurately predict VO across different exercise intensities by combining muscle oxygen (MO) with heart rate (HR). Twenty young highly trained athletes performed the following ...

Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach.

Journal of sports sciences
Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a...

A data mining approach for determining biomechanical adaptations in runners who experienced and recovered from patellofemoral pain syndrome.

Journal of sports sciences
Patellofemoral pain (PFP) is a common musculoskeletal pain disorder experienced by runners. While biomechanics of those with PFP have been extensively studied, methodological considerations may omit important adaptations exhibited by those experienci...