ArticleEndoscopy international open2025
GastroGPT: Development and controlled testing of a proof-of-concept customized clinical language model.
Article in Endoscopy international open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- GastroGPT Pioneering Specialized AI in Gastroenterology: Strengths, Pitfalls, and the Road to Clinical Integration.JGH open : an open access journal of gastroenterology and hepatology · 2025Article
- Machine learning in gastrointestinal endoscopy: challenges and opportunities.BMJ open gastroenterology · 2025Review
- A Novel Ensemble Framework for Comprehensive Early-Stage Colorectal Cancer Diagnosis, Prognosis, and Treatment: Integration of Gastroenterology-Specific Transformer Language Models and Multiple Decision Trees.Journal of clinical medicine · 2025Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and study aims: Current general-purpose artificial intelligence (AI) large language models (LLMs) demonstrate limited efficacy in clinical medicine, often constrained to question-answering, documentation, and literature summarization roles. We developed GastroGPT, a proof-of-concept specialty-specific, multi-task, clinical LLM, and evaluated its performance against leading general-purpose LLMs across key gastroenterology tasks and diverse case scenarios. Methods: In this structured analysis, GastroGPT was compared with three state-of-the-art general-purpose LLMs (LLM-A: GPT-4, LLM-B: Bard, LLM-C: Claude). Models were assessed on seven clinical tasks and overall performance across 10 simulated gastroenterology cases varying in complexity, frequency, and patient demographics. Standardized prompts facilitated structured comparisons. A blinded expert panel rated model outputs per task on a 10-point Likert scale, judging clinical utility. Comprehensive statistical analyses were conducted. Results: A total of 2,240 expert ratings were obtained. GastroGPT achieved significantly higher mean overall scores (8.1 ± 1.8) compared with GPT-4 (5.2 ± 3.0), Bard (5.7 ± 3.3), and Claude (7.0 ± 2.7) (all Conclusions: This study pioneered development and comparison of a specialty-specific, clinically-oriented AI model to general-purpose LLMs. GastroGPT demonstrated superior utility overall and on key gastroenterology tasks, highlighting the potential for tailored, task-focused AI models in medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.