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. 2025 May 20.
doi: 10.14309/ajg.0000000000003552. Online ahead of print.

Artificial Intelligence in Gastroenterology Education: DeepSeek Passes the Gastroenterology Board Examination and Outperforms Legacy ChatGPT Models

Andrew F Ibrahim  1 , Pojsakorn Danpanichkul  2 , Alexander Hayek  1 , Edwin Paul  1 , Annmarie Farag  1 , Masab Mansoor  1 , Charat Thongprayoon  3 , Wisit Cheungpasitporn  3 , Mohamed O Othman  4
Affiliations

Artificial Intelligence in Gastroenterology Education: DeepSeek Passes the Gastroenterology Board Examination and Outperforms Legacy ChatGPT Models

Andrew F Ibrahim et al. Am J Gastroenterol. .

Abstract

Introduction: DeepSeek was evaluated in gastroenterology board examination performance against legacy ChatGPT offline models, which previously showed failing performance.

Methods: The performances of the DeepSeek base R1 model and search-augmented R1 model were assessed using American College of Gastroenterology self-assessments (455 questions).

Results: DeepSeek exceeded the passing threshold. Search-augmented DeepSeek scored 81.5% across all questions, and the R1 base model scored 77.1%. Both search-augmented and offline DeepSeek models surpassed offline ChatGPT-3 (65.1%) and ChatGPT-4 (62.4%) ( P < 0.001).

Discussion: DeepSeek exhibited passing performance on the gastroenterology board examination but had gaps in niche topics and image exclusion limit utility. It may supplement education if validated by specialists.

Keywords: artificial intelligence; large language models; medical education.

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