The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Chat Generative Pretrained Transformer Fails the Multiple-Choice American College of Gastroenterology Self-Assessment Test
Abstract
INTRODUCTION: Chat Generative Pretrained Transformer (ChatGPT) is a natural language processing model that generates human-like text. METHODS: ChatGPT-3 and ChatGPT-4 were used to answer the 2022 and 2021 American College of Gastroenterology self-assessment tests. The exact questions were inputted in both versions of ChatGPT. A score of 70% or higher was required to pass the assessment. RESULTS: Overall, ChatGPT-3 scored 65.1% on 455 included questions and GPT-4 scored 62.4%. DISCUSSION: ChatGPT did not pass the American College of Gastroenterology self-assessment test. We do not recommend its use for medical education in gastroenterology in its current form.
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“While these models offer powerful foundational capabilities, adapting them to specific tasks and datasets without losing robustness is a significant hurdle, often resulting in significant variability in accuracy across different settings.7,9,10”
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ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
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ChatGPT for good? On opportunities and challenges of large language models for education
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Vision, challenges, roles and research issues of Artificial Intelligence in Education
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Medical Education Must Move From the Information Age to the Age of Artificial Intelligence
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Aye, AI! ChatGPT passes multiple-choice family medicine exam
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A scoping review of artificial intelligence in medical education: BEME Guide No. 84
Gordon, M., Daniel, M., Ajiboye, A., Uraiby, H., Xu, N. Y., Bartlett, R., Hanson, J., Haas, M., Spadafore, M., Grafton-Clarke, C., et al. (2024) · Medical Teacher · doi:10.1080/0142159x.2024.2314198 · Cited by 679
Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis
Wei, Q., Yao, Z., Cui, Y., Wei, B., Jin, Z., & Xu, X. (2024) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2024.104620 · Cited by 233
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A Systematic Review of the Limitations and Associated Opportunities of ChatGPT
Cong‐Lem, N., Soyoof, A., & Tsering, D. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2344142 · Cited by 140
Metadata
- Authors
- Suchman, K., Garg, S., & Trindade, A. J.
- Affiliations
- Northwell Health (US)
- Arkansas Gastroenterology, North Little Rock, Arkansas, USA;
- Corresponding author
- Trindade, Arvind J.
- Venue
- American Journal of Gastroenterology
- Published
- 2023-05-22
- Volume
- 118
- Issue
- 12
- Pages
- 2280-2282
- ISSN
- 0002-9270 (ISSN-L)
- 1572-0241
- OpenAlex
- W4377220156
- Cited by
- 139
- References
- 7
- Citations by year
- 2026: 13 · 2025: 32 · 2024: 61 · 2023: 32
- FWCI
- 5.59
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The American Journal of Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Innovations in Medical Education
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- ChatGPT, large language models, gastroenterology education, medical knowledge assessment, ChatGPT-3, ChatGPT-4, artificial intelligence in medical education
- MeSH terms
- Gastroenterology, Humans, Self-Assessment, Universities
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