Evaluating a Foundation Artificial Intelligence Model for Glaucoma Detection Using Color Fundus Photographs
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Authors
- Christopher A. Girkin (ORCID: https://orcid.org/0000-0002-5781-7682)
- Benton Chuter (ORCID: https://orcid.org/0000-0002-0354-0569)
- Robert Neal Weinreb (ORCID: https://orcid.org/0000-0001-9553-3202)
- Evan Walker (ORCID: https://orcid.org/0000-0001-8566-0371)
- Massimo A. Fazio (ORCID: https://orcid.org/0000-0002-7489-089X)
- Linda M. Zangwill (ORCID: https://orcid.org/0000-0002-1143-5224)
- Justin Huynh (ORCID: https://orcid.org/0000-0002-4640-6124)
- Shahin Hallaj (ORCID: https://orcid.org/0000-0002-9541-1915)
- Mark Christopher
- Jeffrey M Liebmann
Institutions
- University of Illinois Urbana-Champaign (US)
- University of Alabama at Birmingham (US)
- University of California San Diego (US)
- New York Glaucoma Research Institute (US)
Publication Details
- Journal
- Ophthalmology Science
- Published
- 2024-09-14
- DOI
- https://doi.org/10.1016/j.xops.2024.100623
- Citations
- 10
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 4.04
Funders
- Research to Prevent Blindness
- Glaucoma Foundation
- Heidelberg Engineering
- National Institutes of Health
- University of California, San Diego
- Common Fund