Assessment of a Large Language Model’s Responses to Questions and Cases About Glaucoma and Retina Management

Key Points Question Can a large language model (LLM) chatbot provide accurate and complete responses compared with fellowship-trained ophthalmologists in managing glaucoma and retina diseases? Findings In this cross-sectional study, with responses graded using a Likert scale, the LLM chatbot demonstrated comparative proficiency, largely matching if not outperforming glaucoma and retina subspecialists in addressing ophthalmological questions and patient case management. Meaning The findings underscore the potential utility of LLMs as valuable diagnostic adjuncts in ophthalmology, particularly in highly specialized and surgical subspecialties of glaucoma and retina.