Evaluating the performance of GPT-3.5, GPT-4, and GPT-4o in the Chinese National Medical Licensing Examination

Abstract

This study aims to compare and evaluate the performance of GPT-3.5, GPT-4, and GPT-4o in the 2020 and 2021 Chinese National Medical Licensing Examination (NMLE), exploring their potential value in medical education and clinical applications. Six hundred original test questions from the 2020 and 2021 NMLE (covering five types of questions) were selected and input into GPT-3.5, GPT-4, and GPT-4o for response. The accuracy of the models across different question types and units was recorded and analyzed. Statistical methods were employed to compare the performance differences among the three models. GPT-4o demonstrated significantly higher overall accuracy than GPT-4 and GPT-3.5 (P < 0.001). In the 2020 and 2021 exams, GPT-4o achieved accuracy rates of 84.2% and 88.2%, respectively, with the highest accuracy observed in questions related to the digestive system (Unit 3), reaching 94.75%. GPT-4 showed moderate performance, while GPT - 3.5 had the lowest accuracy. Additionally, GPT-4o exhibited a clear advantage in complex question formats, such as case analysis questions (A3/A4 type) and standard matching questions (B1 type). GPT-4o outperformed its predecessors in the NMLE, demonstrating exceptional comprehension and problem-solving abilities in non-English medical examinations. This study provides important insights into the application and promotion of generative AI in medical education and clinical practice.

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