Artificial intelligence (AI) is bringing about transformative changes in orthopedic surgery, with its potential being particularly prominent in the field of fracture and trauma treatment. This review explores the current applications and future prospects of AI-driven surgical planning and simulation, robot and image-based navigation surgery, and image-assisted diagnostic technologies. Robotic assistance in orthopedic surgery, which was initially applied to improve accuracy in component implantation for knee and hip arthroplasty and to achieve high precision in spinal screw placement, has recently expanded its use to include accurate, minimally invasive reduction of pelvic fractures. In diagnostics, AI aids in the early prediction and classification of ambiguous fractures in various anatomical regions—for example, detecting shoulder or hip fractures, identifying incomplete atypical femur fractures, and classifying femoral neck fractures—through X-ray image analysis. This improves diagnostic accuracy and reduces medical costs. However, significant challenges remain, including high initial costs, steep learning curves, a lack of long-term studies, data bias, and ethical concerns. Continued research, interdisciplinary collaboration, and policy support are crucial for the widespread adoption of these technologies.
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AI-Assisted Fracture Detection in Orthopedic and Trauma Imaging: Where It Works, Where It Fails, and Principles for Safe Clinical Deployment Wojciech Michał Glinkowski, Paweł Kaminski, Rafał Obuchowicz Diagnostics.2026; 16(10): 1420. CrossRef