Purpose This study aimed to assess the performance of ChatGPT, specifically the GPT-3.5 and GPT-4 models, on the Korean general surgery board exam questions and investigate the potential applications of large language models (LLM) for surgical education and training. Method The dataset comprised 280 questions from the Korean general surgery board exams conducted between 2020 and 2022. Both GPT-3.5 and GPT-4 models were evaluated, and their performance was compared using the chi-square test. Result GPT-3.5 achieved an overall accuracy of 46.8%, while GPT-4 demonstrated a significant improvement with an overall accuracy of 76.4%, indicating a notable difference in performance between the models (p<.001). GPT-4 also exhibited consistent performance across all subspecialties, with accuracy rates ranging from 63.6% to 83.3%. Conclusion ChatGPT, particularly GPT-4, demonstrates a remarkable ability to understand complex surgical clinical information, achieving an accuracy rate of 76.4% on the Korean general surgery board exam. As LLM technology continues to advance, its potential applications in surgical education, training, and continuous medical education (CME) are anticipated to enhance patient outcome and safety.

The authors have declared no competing interest.

This study was supported by Future Medicine 2030 Project of the Samsung Medical Center [SMX1230771]

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