Related Experiment Video
Updated: Jun 14, 2025
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Artificial Intelligence in Gastroenterology Education: DeepSeek Passes the Gastroenterology Board Examination and
Andrew F Ibrahim1, Pojsakorn Danpanichkul2, Alexander Hayek1
1School of Medicine, Texas Tech University Health Sciences Center, Lubbock, Texas, USA.
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.
