A Novel Multimodal Implementation of a Foundation Artificial Intelligence Model Using Optic Nerve Head Fundus Photographs and OCT Imaging for Glaucoma Detection

Purpose: To compare the performance of unimodal and multimodal implementation of the self-supervised learning model RETFound in detecting glaucoma using color fundus photographs (CFPs) and OCT images, and to assess its generalizability across different ethnicities, age groups, and disease severities...

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Главные авторы:	Benton Chuter, MD, Vedant Joshi, MS, Shahin Hallaj, MD, Evan Walker, MS, Christopher Bowd, PhD, Akram Belghith, PhD, Michael H. Goldbaum, MD, Andrzej Grzybowski, MD, PhD, Massimo A. Fazio, PhD, Christopher A. Girkin, MD, C. Gustavo De Moraes, MD, PhD, Jeffrey M. Liebmann, MD, Robert N. Weinreb, MD, Linda M. Zangwill, PhD, Mark Christopher, PhD
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2026-02-01
Серии:	Ophthalmology Science
Предметы:	Artificial intelligence Foundation model Fundus photographs Multimodal OCT
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S2666914525003100
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