Evaluating Large Language Models in Ptosis-Related inquiries: A Cross-Lingual Study
This study bridges artificial intelligence (AI) advancements with clinical practice by demonstrating how optimized LLMs can enhance patient education and cross-linguistic clinician support tools in ptosis-related inquiries.
Authors
- Luyuan Niu
- Wei Li (ORCID: https://orcid.org/0000-0002-9339-7267)
- Yueqing He
- Li Dong (ORCID: https://orcid.org/0000-0003-0120-5756)
- Dongmei Li (ORCID: https://orcid.org/0000-0001-7466-9020)
- L Wang (ORCID: https://orcid.org/0000-0003-0545-2308)
- Mingyang Wang (ORCID: https://orcid.org/0000-0001-7201-5090)
- Lan Ma
- Xue Jiang (ORCID: https://orcid.org/0000-0003-1529-5617)
- Bing Qin (ORCID: https://orcid.org/0000-0002-9040-5866)
- Tao Chen (ORCID: https://orcid.org/0009-0006-4934-1246)
- Jialu Geng
Institutions
- Twitter (United States) (US)
- Beijing Tongren Hospital (CN)
- He Eye Hospital (CN)
- China Minmetals (China) (CN)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-07-16
- DOI
- https://doi.org/10.1167/tvst.14.7.9
- Primary Topic
- Medical and Biological Sciences
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Sanming Project of Medicine in Shenzhen