Comparing ChatGPT3.5 and Bard recommendations for colonoscopy intervals: Bridging the gap in healthcare settings
This study highlights the limitations of freely available LLMs in assisting colonoscopy screening recommendations. Although the potential of freely available LLMs to offer uniformity is significant, the low accuracy, as noted, excludes their use as the sole agent in providing recommendations.
Authors
- Jennifer L. Dodge
- Patrick Chang (ORCID: https://orcid.org/0000-0003-4675-6404)
- Ara Sahakian (ORCID: https://orcid.org/0000-0002-2665-6724)
- Jennifer Phan (ORCID: https://orcid.org/0000-0001-9963-5580)
- Maziar Amini
- James Buxbaum (ORCID: https://orcid.org/0000-0003-0868-5238)
- Rio O. Davis
- Denis Nguyen
Institutions
- Tulane University (US)
- University of Southern California (US)
- University of California, San Francisco (US)
Publication Details
- Journal
- Endoscopy International Open
- Published
- 2025-04-14
- DOI
- https://doi.org/10.1055/a-2586-5912
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65