BMC medical informatics and decision making · 2026 · 範疇回顧（依標題推測）
Artificial intelligence and machine learning in sports medicine: mapping clinical tasks and assessing clinical maturity - a scoping review.
其他（運動科學・政策・牙科等） · 運動醫學人工智慧
中文閱讀摘要
本範圍性回顧指出運動醫學AI多用於骨科與神經科，雖樣本內表現佳但多為回顧性驗證，目前僅宜作輔助工具。
AI 依來源摘要整理，未經人工逐篇核對。閱讀結論前，請回溯研究族群、方法與限制。
原始摘要
Background
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming the medical field. The aim of this review was to outline the current scientific state of AI and ML application in sports medicine, evaluate the level of clinical validation and readiness for implementation, and identify key priorities to guide future advancements and implementation into injury risk assessment, diagnosis, rehabilitation and clinical decision-making in sport medicine.
Methods
A scoping review was conducted with a literature search performed on February 5, 2026, using the MEDLINE, EMBASE and Web of Science databases which targeted AI or ML application on individuals within a sports medicine context.
Results
Of 8,677 studies, 97 studies were included. Most research covered orthopaedics (70.1%) and neurology (18.6%), where AI was applied for injury prediction, diagnostic image analysis, and recovery estimation. Predictive and estimation models were the dominant application (57.7%). Reported discriminative performance was frequently high. However, the majority of studies relied on retrospective datasets and internal validation. Calibration reporting was uncommon, and prospective workflow integration was rare, with a single study attempting an interventional prevention strategy. Substantial heterogeneity in modelling approaches, data inputs, and outcomes definitions was observed.
Conclusion
Although AI and ML applications in sports medicine frequently demonstrate strong within-sample performance, most remain in early-stage development. Currently, these tools should be viewed as supportive adjuncts rather than autonomous decision-making systems.
Key terms
AI, Predictive modeling, Diagnostic imaging, Rehabilitation, Deep learning, Return to sport.
至 Europe PMC 閱讀完整來源 ↗ · 擷取日期 2026-10-19
書目、來源與全文狀態
- DOI
- 10.1186/s12911-026-03615-w
- PMID／PMCID
- 42286628 / PMC13263937
- 作者
- Lindskog J, Heder Ternell K, Yu Y, Lindman I, Samuelsson K, Hamrin Senorski E
- 首次發表日期
- 2026-06-12Europe PMC 提供，部分日期可能依年份或月份推定。
- 卷／期／頁碼或文章編號
- 26 ／ 1 ／ 212
- 書目來源與查核日期
- Europe PMC · 2026-10-19僅核對書目欄位與來源連結；不代表已評讀研究品質。
- 全文與授權
- 來源列有免費全文（查核 2026-10-19），未逐篇測試 PDF 下載。 來源授權標示：cc by。
可回溯引用
Lindskog J, Heder Ternell K, Yu Y, Lindman I, Samuelsson K, Hamrin Senorski E. Artificial intelligence and machine learning in sports medicine: mapping clinical tasks and assessing clinical maturity - a scoping review. BMC medical informatics and decision making. 2026;26(1):212. PMID: 42286628. PMCID: PMC13263937. doi:10.1186/s12911-026-03615-w
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