Large Language Models Triage of Retina Patient Emergency Telephone Calls: A Pilot Study.

ABSTRACT: Purpose: To compare the diagnostic and management accuracy of large language model chatbots vs that of humans in performing outpatient retina triage in on-call telephone emergencies. Methods: Four large language model chatbots, 3 vitreoretinal surgery fellows, and 3 certified ophthalmic technicians with on-call experience were presented with 10 simulated retina cases representing after-hours telephone calls from patients. Diagnosis and triage recommendations were obtained from chatbots and humans. Recommendations were graded for each chatbot and human respondent. Results: Human graders were significantly more accurate than chatbots in diagnosis (95% vs 76.7%, respectively; P < .01) and follow-up recommendations (85% vs 70%, respectively; P = .03). However

SUBMITTER: Chahal R 

PROVIDER: S-EPMC12832218 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature