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This study compares the performance of three language models in Traditional Chinese Medicine licensing examinations to evaluate their effectiveness.

April 20, 2026Scientific ReportsOpen Access

Three large language models demonstrate competitive performance in Traditional Chinese Medicine national medical licensing examinations over two years

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This study compares the performance of three language models in Traditional Chinese Medicine licensing examinations to evaluate their effectiveness.
Evaluated accuracy of Gemini 3 Pro, DeepSeek V3.1, and GPT-5.2 on two years of TCM licensing examination questions.
Conducted chi-square tests for comparative analysis across models and question types.
Input all 600 examination questions from 2023 and 2024 into each model.
DeepSeek V3.1 achieved the highest accuracy in both years (87.1% in 2023 and 86.7% in 2024).
Gemini 3 Pro showed moderate and stable performance, while GPT-5.2 had the lowest scores, despite some improvement.
DeepSeek V3.1 excelled particularly in structured and clinically oriented questions.

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Implication

Comparative analysis of language models shows significant performance variations in Traditional Chinese Medicine exams, highlighting educational implications.

Cite This Study

Du et al. (2026) studied this question.

synapsesocial.com/papers/69e5c22d03c29399140288ee https://doi.org/10.1038/s41598-026-49200-z

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Implication

Comparative analysis of language models shows significant performance variations in Traditional Chinese Medicine exams, highlighting educational implications.

Three large language models demonstrate competitive performance in Traditional Chinese Medicine national medical licensing examinations over two years

Key Points

Discussion

Implication

Cite This Study

Three large language models demonstrate competitive performance in Traditional Chinese Medicine national medical licensing examinations over two years

Key Points

Discussion

Implication

Cite This Study

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