Enhancing Hand Fracture Care: A Prospective Study of Artificial Intelligence Application With ChatGPT

Abstract

Purpose: The integration of artificial intelligence and machine learning technologies into the medical field has brought about remarkable advancements, particularly in the domain of clinical decision support systems. However, it is uncertain how they will perform as clinical decision-makers. Methods: This prospective cohort study evaluates the potential of incorporating ChatGPT-4 plus into the management of subcapital fifth metacarpal fractures. The treatment recommendations provided by ChatGPT-4 plus were compared with those of the two control groups-the attending clinic plastic surgeon and an independent expert panel. The primary outcome measures, operative or conservative, were compared between the groups. Intraclass correlation of 0.61 infers moderate reliability in the consistency of recommended management plans across all groups. Results: Key predictors for opting for operative management, regardless of the decision-maker, included clinical signs of scissoring, extension deficit, and radiographic evidence of intra-articular extension. Conclusions: These findings support the potential for artificial intelligence applications in enhancing diagnostic and treatment decisions. Type of study/level of evidence: Therapeutic IV.

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