Expert review highlights artificial intelligence applications in musculoskeletal surgery, indicating the need for robust validation and ethical governance to ensure patient safety.
Key Points
To examine the translation of artificial intelligence technologies into musculoskeletal surgery and define prerequisites for responsible, evidence-based clinical adoption.
Narrative review evaluating artificial intelligence integration across orthopedic diagnostic imaging, pre-operative planning, robotic-assisted surgery, and post-operative monitoring.
Analysis of technical modalities, including machine learning algorithms, deep learning models, computer vision, and generative artificial intelligence in surgical workflows.
Artificial intelligence expands diagnostic precision, operative planning, intraoperative navigation, and outcome prediction by detecting complex patterns across multidimensional clinical datasets.
Clinical utility depends on rigorous algorithmic validation, ethical governance, transparency, and preservation of surgeon-led decision-making rather than technological capability alone.