Evaluating the Efficacy of Large Language Models in Guiding Treatment Decisions for Pediatric Refractive Error
ChatGPT-4o showed better accuracy and clinical safety, making it a promising tool for decision support in pediatric ophthalmology, although expert oversight is still necessary.
Authors
- Jia Feng (ORCID: https://orcid.org/0000-0003-1168-0518)
- Andrzej E. Grzybowski (ORCID: https://orcid.org/0000-0002-3724-2391)
- Kai Jin (ORCID: https://orcid.org/0000-0003-4369-2417)
- Wenyue Shen (ORCID: https://orcid.org/0000-0002-1352-9419)
- Daohuan Kang
- Lu Yuan (ORCID: https://orcid.org/0000-0001-7879-0389)
- Jiao Zhan (ORCID: https://orcid.org/0009-0003-8519-2207)
- Wen Sun (ORCID: https://orcid.org/0009-0005-3897-8922)
- Hongkang Wu
Institutions
- Zhejiang Technical Institute of Economics (CN)
- Children's Hospital of Zhejiang University (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
Publication Details
- Journal
- Ophthalmology and Therapy
- Published
- 2025-02-22
- DOI
- https://doi.org/10.1007/s40123-025-01105-2
- Citations
- 12
- Primary Topic
- Ophthalmology and Visual Health Research
- Type
- article
- Field-Weighted Citation Impact
- 20.48
Funders
- National Natural Science Foundation of China