Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: Comparison Study

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Conflicts of Interest

Identified Weaknesses

Rating Explanation

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Paper Summary

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GPT-4 Passes the Japanese Medical Licensing Exam! (But GPT-3.5 Failed)

GPT-4 achieved a passing score on the Japanese Medical Licensing Examination (JMLE), while GPT-3.5 did not. This highlights the significant improvement in GPT-4's ability to process complex medical information in a non-English language, surpassing GPT-3.5 in various question types and difficulty levels.

Possible Conflicts of Interest

None identified

Identified Weaknesses

Time-Sensitive Results

The study acknowledges that the results are time-sensitive and that the performance of ChatGPT, particularly GPT-4, is expected to improve rapidly. This limits the generalizability of the findings.

Exclusion of Image and Table-Based Questions

The exclusion of questions with images and tables, while necessary for comparison between GPT-3.5 and GPT-4, does not reflect the real-world application of these models in medical contexts where such visual information is crucial.

Limited Focus on ChatGPT

The study focuses solely on ChatGPT and does not consider other large language models. This limits the scope of the findings and prevents broader conclusions about the capabilities of LLMs in medical education and practice.

Limited Generalizability

The study uses a single, specific examination (JMLE) in a specific language (Japanese). This limits the generalizability of the findings to other medical examinations and other languages.

Limited Discussion of Hallucinations

The study does not address the issue of "hallucinations" in detail, which is a significant concern with LLMs, especially in the context of medical information where accuracy is paramount.

Rating Explanation

This study provides a valuable comparison of GPT-3.5 and GPT-4's performance on a real-world medical licensing examination. The methodology is sound, and the findings are relevant to the application of LLMs in medical education. While the limitations regarding generalizability and the rapidly evolving nature of LLMs are acknowledged, the study's focus on a non-English language adds to the existing literature. The study's focus, direct applicability, and the significant performance difference found justify a rating of 4.

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