Assessing the proficiency of large language models on funduscopic disease knowledge

Assessing the proficiency of large language models on funduscopic disease knowledge

AIM: To assess the performance of five distinct large language models (LLMs; ChatGPT-3.5, ChatGPT-4, PaLM2, Claude 2, and SenseNova) in comparison to two human cohorts (a group of funduscopic disease experts and a group of ophthalmologists) on the specialized subject of funduscopic disease. METHODS:...

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Bibliographic Details
Main Authors: Jun-Yi Wu, Yan-Mei Zeng, Xian-Zhe Qian, Qi Hong, Jin-Yu Hu, Hong Wei, Jie Zou, Cheng Chen, Xiao-Yu Wang, Xu Chen, Yi Shao
Format: Article
Language:English
Published: Press of International Journal of Ophthalmology (IJO PRESS) 2025-07-01
Series:International Journal of Ophthalmology
Subjects:
large language models
chatgpt
funduscopic disease
Online Access:http://ies.ijo.cn/en_publish/2025/7/20250703.pdf
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