Shanghai Eye Disease Prevention & Treatment Center

Evaluating the effectiveness of large language models in patient education for conjunctivitis

Jingyuan Wang, Runhan Shi, Qihua Le et al.

2024 · 15 Zit.

Medical Staff and Resident Preferences for Using Deep Learning in Eye Disease Screening: Discrete Choice Experiment

Senlin Lin, Liping Li, Haidong Zou et al.

2022 · 11 Zit.

Assessing the possibility of using large language models in ocular surface diseases

Qian Ling, Yan-Mei Zeng, Hong Qi et al.

2024 · 10 Zit.

Performance of popular large language models in glaucoma patient education: A randomized controlled study

Yuyu Cao, Wei Lü, Runhan Shi et al.

2024 · 5 Zit.

[Challenges of artificial intelligence used for eye disease screening in recent China communities].

Hao Zou, Lina Lu, Yuanyuan Xu et al.

2022 · 3 Zit.

Transforming cataract care through artificial intelligence: an evaluation of large language models’ performance in addressing cataract-related queries

Xinyue Wang, Yan Liu, Linghao Song et al.

2025 · 1 Zit.

Correction: Evaluating multiple large language models on orbital diseases.

Qichen Yang, Yan-Mei Zeng, Hong Wei et al.

2025 · 0 Zit.

Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review

Senlin Lin, Juzhao Zhang, Catherine Jan et al.

2025 · 0 Zit.

Evaluating multiple large language models on orbital diseases

Qichen Yang, Yan-Mei Zeng, Hong Wei et al.

2025 · 0 Zit.

Comparing the performance of four mainstream large language models on medical literature review generation: a human expert evaluation in SMILE surgery

Mengyun Zhou, Fu Gui, Chong Ai et al.

2026 · 0 Zit.

Assessing the proficiency of large language models on funduscopic disease knowledge

Jun-Yi Wu, Xian-Zhe Qian, Qi Hong et al.

2025 · 0 Zit.