Assessing the Clinical Utility of Multimodal Large Language Models in the Diagnosis and Management of Pigmented Choroidal Lesions
This study highlights limitations and potential of MLLMs in aiding diagnosis and treatment of choroidal lesions.
Authors
- Nehal Nailesh Mehta (ORCID: https://orcid.org/0000-0003-4653-2021)
- Shyamanga Borooah (ORCID: https://orcid.org/0000-0003-2970-045X)
- Akshay Agnihotri (ORCID: https://orcid.org/0009-0001-4624-8250)
- Evan Walker (ORCID: https://orcid.org/0000-0001-8566-0371)
- Melanie Tran
- Michael H. Goldbaum (ORCID: https://orcid.org/0000-0002-7721-2736)
- Ines Doris Nagel (ORCID: https://orcid.org/0000-0002-4649-6764)
- Nathan L. Scott (ORCID: https://orcid.org/0000-0002-0746-2860)
- Elena Flester
- Gillian A. Folk
Institutions
- University of California San Diego (US)
- Smith-Kettlewell Eye Research Institute (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1167/tvst.14.10.13
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00