ReviewCurrent reviews in musculoskeletal medicine2026
Artificial Intelligence and its Current Role in Clinical Outcome Prediction, Musculoskeletal Imaging, and Economic and Ethical Considerations within Orthopedics and Sports Medicine.
Review in Current reviews in musculoskeletal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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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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Authors and funding
7 authors.
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Abstract
purpose of reviewArtificial intelligence (AI) has emerged as a useful tool across the field of orthopedic surgery. This review highlights recent literature on AI’s role in surgical outcome prediction, musculoskeletal imaging, economic and ethical considerations, with a focus on its integration in sports medicine workflow and procedures. RECENT
findingsMachine learning AI models have demonstrated superior accuracy in predicting orthopedic related patient-reported outcomes, surgical complications, and the utilization of healthcare compared to traditional, non-AI methods. Within imaging, AI applications now produce automated measurements for clinical and presurgical planning with precision equivalent to expert-level measurements. Large language AI models are increasingly used for clinical documentation, research workflows, and administrative support for healthcare delivery and effectiveness. Despite increasing integration of AI into orthopedics and its subspecialties, challenges in validation, accessibility due to cost, and ethical considerations remain. Orthopedic surgery and sports medicine are particularly well suited for AI applications due to their well-defined, measurable clinical outcomes. Emerging AI tools and models show promise in enhancing patient outcomes, surgical planning, and healthcare efficiency. Continued AI research must prioritize external validation, ethical implementation, and educational integration to ensure responsible, effective, and reproducible use.
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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.