Leveraging Large Language Models with Sequential Prompting to Extract Eye Examination Findings from Free-Text Ophthalmology Notes
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Authors
- Sophia Ying Wang (ORCID: https://orcid.org/0000-0003-0916-9403)
- Robert T. Chang (ORCID: https://orcid.org/0000-0002-2950-7951)
- Fang Ruan (ORCID: https://orcid.org/0000-0002-9386-3774)
- Houri Esmaeilkhanian (ORCID: https://orcid.org/0000-0002-7877-217X)
- Janice Lam
Institutions
- Smith-Kettlewell Eye Research Institute (US)
- Stanford University (US)
Publication Details
- Journal
- Ophthalmology Science
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1016/j.xops.2025.100944
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Research to Prevent Blindness
- American Glaucoma Society
- Alcon Research Institute