Can OpenAI's New o1 Model Outperform Its Predecessors in Common Eye Care Queries?
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Authors
- Victor Koh (ORCID: https://orcid.org/0000-0003-4134-7142)
- David Ziyou Chen (ORCID: https://orcid.org/0000-0002-2153-3100)
- Wendy Wong (ORCID: https://orcid.org/0000-0002-4514-250X)
- Chen‐Hsin Sun
- George N. Thomas (ORCID: https://orcid.org/0000-0003-1827-4707)
- Yien Lai
- Krithi Pushpanathan (ORCID: https://orcid.org/0000-0001-6263-8489)
- Marcus Chun Jin Tan (ORCID: https://orcid.org/0000-0002-4849-6194)
- Sahana Srinivasan (ORCID: https://orcid.org/0009-0004-9355-6717)
- Yih Chung Tham (ORCID: https://orcid.org/0000-0002-6752-797X)
- Weizhi Ma (ORCID: https://orcid.org/0000-0001-5604-7527)
- Minjie Zou (ORCID: https://orcid.org/0000-0002-1955-0737)
- Hazel Anne Hui'En Lin
- Janice Sing Harn Lam
- Erlangga Ariadarma Mangunkusumo
Institutions
- National University of Singapore (SG)
- Singapore National Eye Center (SG)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- National University Hospital (SG)
- National University Health System (SG)
- Tsinghua University (CN)
Publication Details
- Journal
- Ophthalmology Science
- Published
- 2025-02-22
- DOI
- https://doi.org/10.1016/j.xops.2025.100745
- Citations
- 10
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 8.06
Funders
- National University of Singapore
- National Research Foundation Singapore
- National Medical Research Council