Objective To determine the appropriateness of ophthalmology recommendations from an
online chat-based artificial intelligence model to ophthalmology questions. Patients and�…

Importance Large language models (LLMs) like ChatGPT appear capable of performing a
variety of tasks, including answering patient eye care questions, but have not yet been�…

Purpose Patients are using online search modalities to learn about their eye health. While
Google remains the most popular search engine, the use of large language models (LLMs)�…

Importance Large language models (LLMs) are revolutionizing medical diagnosis and
treatment, offering unprecedented accuracy and ease surpassing conventional search�…

PURPOSE To investigate the ability of generative artificial intelligence models to answer
ophthalmology board–style questions. DESIGN Experimental study. METHODS This study�…

Purpose To assess the accuracy of ophthalmic information provided by an artificial
intelligence chatbot (ChatGPT). Methods Five diseases from 8 subspecialties of�…

Objective The aim of this study was to evaluate the accuracy, comprehensiveness, and
safety of a publicly available large language model (LLM)—ChatGPT in the sub-domain of�…

Background As advancements in artificial intelligence (AI) continue, large language models
(LLMs) have emerged as promising tools for generating medical information. Their rapid�…

Purpose: To assess the alignment of GPT-4-based evaluation to human clinician experts, for
the evaluation of responses to ophthalmology-related patient queries generated by fine�…

Importance Although augmenting large language models (LLMs) with knowledge bases
may improve medical domain–specific performance, practical methods are needed for local�…