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Glaucoma Detection and Feature Identification via GPT-4V Fundus Image Analysis

Purpose: The aim is to assess GPT-4V's (OpenAI) diagnostic accuracy and its capability to identify glaucoma-related features compared to expert evaluations. Design: Evaluation of multimodal large language models for reviewing fundus images in glaucoma. Subjects: A total of 300 fundus images from 3 p...

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Principais autores: Jalil Jalili, PhD, Anuwat Jiravarnsirikul, MD, Christopher Bowd, PhD, Benton Chuter, MD, Akram Belghith, PhD, Michael H. Goldbaum, MD, Sally L. Baxter, MD, Robert N. Weinreb, MD, Linda M. Zangwill, PhD, Mark Christopher, PhD
Format: Artigo
Jezik:Inglês
Izdano: Elsevier 2025-03-01
Serija:Ophthalmology Science
Teme:
Artificial intelligence
Fundus image analysis
Glaucoma detection
GPT-4V
Large multimodal models
Online dostop:http://www.sciencedirect.com/science/article/pii/S2666914524002033
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