Generative Artificial Intelligence for Trauma and Fracture Surgery: Assessing the Efficacy of AI-Assisted Decision Support for Orthopedic Surgeons

Generative Artificial Intelligence (AI) has emerged as a potential decision-support tool in trauma and fracture surgery, yet its efficacy in real-world clinical contexts remains underexplored. This study systematically identified critical information needs of orthopedic trauma surgeons and evaluated the performance of five leading AI models (ChatGPT-۴, Gemini, Claude, Med-PaLM, and BioGPT) in addressing these needs. Through a three-phase approach—literature review, AI querying, and blinded expert evaluation—we assessed accuracy, relevance, hallucination rates, and response times. Results indicated ChatGPT-۴ outperformed other models in accuracy (mean score: ۱.۸۰/۲) and relevance (۴.۴۰/۵), with lower hallucination rates (۱۰%). Med-PaLM and BioGPT also demonstrated strong performance, while Gemini and Claude lagged. All models provided responses within clinically acceptable timeframes (<۳۰ seconds). Findings suggest that while AI can offer rapid, guideline-concordant support, human oversight remains essential due to inconsistencies and hallucination risks. Future integration should focus on workflow-embedded, validated systems with continuous monitoring.

کلیدواژه ها:

generative AI ، Trauma Surgery ، Fracture Management ، Decision Support ، Orthopedics