AI-generated text may have a role in evidence-based medicine
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The need to learn about the shortcomings of GAI and specific ideas for incorporating GAI into existing educational strategies were consistent with the recommendations of experts.
“Among the study’s findings, the need to learn about the shortcomings of GAI and some of the specific ideas for incorporating GAI into existing educational strategies were consistent with the recommendations of experts [34].”
From Developing Medical Education Curriculum Reform Strategies to Address the Impact of Generative AI: Qualitative Study (2023) · cites this paper as [34]
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References 8 · Cited by 64
Research works printed but not linked: 3
- Gao CA et al. npj Digit. Med 6, 1-5 (2023). [PubMed: 36596833]
- Hedderich MA et al. In Proc. 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies 2545-2568 (2021).
- Elliot J et al. Nature 600, 383-385 (2021). [PubMed: 34912079]
- Authors
- Peng, Y., Rousseau, J. F., Shortliffe, E. H., & Weng, C.
- Affiliations
- Weill Cornell Medicine (US)
- The University of Texas at Austin (US)
- Columbia University (US)
- Columbia University Irving Medical Center (US)
- Corresponding author
- Peng, Yifan
- Rousseau, Justin F.
- Shortliffe, Edward H.
- Weng, Chunhua
- Venue
- Nature Medicine
- Published
- 2023-05-23
- Volume
- 29
- Issue
- 7
- Pages
- 1593-1594
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- PMC
- PMC11193148
- OpenAlex
- W4377820139
- Cited by
- 64
- References
- 8
- Citations by year
- 2026: 11 · 2025: 24 · 2024: 21 · 2023: 8
- FWCI
- 2.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Health; Human Services | NIH | U.S. National Library of Medicine (4R00LM013001, R01LM009886)
- National Science Foundation (2145640)
- U.S. Department of Health; Human Services | NIH | National Center for Advancing Translational Sciences (UL1TR001873)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Academic Writing and Publishing
- Keywords
- AI-generated text, evidence-based medicine, large language models, human-AI collaboration, foundation models, medical abstracts
- MeSH terms
- Artificial Intelligence, Evidence-Based Medicine, Medical Writing
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