Evolving Consultation: Enhancing Ophthalmic Diagnostic Performance Using Large Language Model.

ABSTRACT:

Objective

Artificial intelligence-powered large language models (LLMs) are increasingly applied in health care. However, studies in ophthalmology assessing whether LLMs can improve the accuracy of complex differential diagnoses in clinical cases, or which levels of clinical experience benefit most from their use, remain lacking. This study assessed the effectiveness of ChatGPT-4o, an LLM-driven chatbot, in enhancing ophthalmologists' clinical reasoning using original scenarios.

Design

Prospective study.

Subjects

Ten original ophthalmic clinical scenarios with open-ended questions were developed, covering the following subspecialties: oculoplastic and orbital disease, glaucoma, inherited retinal disease, macular disease, neuro-ophthalmology, ocular surface, pediatric o

SUBMITTER: Inooka T 

PROVIDER: S-EPMC12919258 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature