Using large language models to generate child-friendly education materials on myopia
Large language models, particularly ChatGPT 4o, hold potential for delivering effective patient education materials on myopia for both adult and pediatric populations. While generally effective, LLMs have limitations for complex medical queries, necessitating continued refinement for reliable clinical use.
Authors
- Tianli Zheng (ORCID: https://orcid.org/0000-0002-2148-5030)
- Xuewei Li (ORCID: https://orcid.org/0000-0002-1596-0720)
- Jie Hu (ORCID: https://orcid.org/0000-0002-0991-9254)
- Yang Deng (ORCID: https://orcid.org/0000-0002-9906-5204)
- Kai Wang (ORCID: https://orcid.org/0000-0002-4171-825X)
- Yan Li (ORCID: https://orcid.org/0000-0001-6155-0389)
- Yixuan Zhang (ORCID: https://orcid.org/0000-0003-3466-0165)
- Sitong Chen (ORCID: https://orcid.org/0000-0002-5159-7957)
- Yuchang Lu
Institutions
- Beijing Institute of Petrochemical Technology (CN)
- Peking University (CN)
- Peking University People's Hospital (CN)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251362338
- Citations
- 1
- Primary Topic
- Ophthalmology and Visual Impairment Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- National Natural Science Foundation of China