Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison
Our findings emphasize the potential of LLMs, particularly ChatGPT-4o, to deliver accurate and comprehensive responses to cataract-related queries, especially in prevention, indicating potential for medical consultation. Continuous efforts to enhance LLMs' accuracy through ongoing strategies and evaluations are essential.
Authors
- Andrzej E. Grzybowski (ORCID: https://orcid.org/0000-0002-3724-2391)
- Kai Jin (ORCID: https://orcid.org/0000-0003-4369-2417)
- Zhijun Luo (ORCID: https://orcid.org/0000-0001-8105-5289)
- Zichang Su (ORCID: https://orcid.org/0009-0004-2917-7317)
- Juan Ye (ORCID: https://orcid.org/0000-0002-1948-2500)
- Hongkang Wu
Institutions
- Second Affiliated Hospital of Zhejiang University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Ophthalmology and Therapy
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1007/s40123-024-01066-y
- Citations
- 18
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.17
Funders
- National Natural Science Foundation of China