Toward Multimodal Conversational AI for Age-Related Macular Degeneration.

Authors

Ran Gu, Benjamin Hou, Mélanie Hébert, Asmita Indurkar, Yifan Yang, Emily Y Chew, Tiarnán D L Keenan, Zhiyong Lu

Published in

Ophthalmology. Retina. Aug 18, 2026. Epub Aug 18, 2026.

Abstract

To evaluate OcularChat, an age-related macular degeneration (AMD)-specific multimodal large language model for interpreting color fundus photographs.
A general-purpose multimodal large language model was fine-tuned using 705,850 simulated patient-physician dialogues paired with 46,167 AREDS images, then tested on separate AREDS and AREDS2 datasets.
In AREDS, OcularChat correctly classified advanced AMD, pigmentary abnormalities, and drusen size in 95.4%, 84.9%, and 67.8% of images, respectively. Retina specialists rated its responses more highly than those of the same model without fine-tuning.
OcularChat gives the potential to support clinician-supervised, interpretable AMD image review, research annotation, and education, requiring prospective validation before clinical deployment.

PMID:
42612872
Bibliographic data and abstract were imported from PubMed on 19 Aug 2026.

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