Performance of popular large language models in glaucoma patient education: A randomized controlled study
Our research identifies Baichuan 2 and ChatGPT-4.0 as prominent LLMs, offering viable options for glaucoma education.
Authors
- Xinwei Xu (ORCID: https://orcid.org/0000-0001-7656-1021)
- Yang Cao (ORCID: https://orcid.org/0000-0002-3552-9153)
- Jiaxu Hong (ORCID: https://orcid.org/0000-0001-9912-633X)
- Xujiao Zhou (ORCID: https://orcid.org/0000-0002-9719-4889)
- Runhan Shi (ORCID: https://orcid.org/0000-0001-7352-2967)
- Jin Yang (ORCID: https://orcid.org/0000-0001-9238-730X)
- Xinghuai Sun (ORCID: https://orcid.org/0000-0002-4440-1389)
- Wei Lü (ORCID: https://orcid.org/0000-0002-0218-569X)
- Steven Liu (ORCID: https://orcid.org/0000-0002-0060-6593)
- Xin Chen (ORCID: https://orcid.org/0009-0004-9357-240X)
- F. Liu
- Guangyu Rong
Institutions
- Hong Kong Baptist University (HK)
- University of Illinois Urbana-Champaign (US)
- Shanghai Eye Disease Prevention & Treatment Center (CN)
- Eye & ENT Hospital of Fudan University (CN)
- State Key Laboratory of Synthetic Chemistry (CN)
- Children's Hospital of Fudan University (CN)
- Qingdao Eighth People's Hospital (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Advances in Ophthalmology Practice and Research
- Published
- 2024-12-03
- DOI
- https://doi.org/10.1016/j.aopr.2024.12.002
- Citations
- 4
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- National Science Fund for Distinguished Young Scholars