医学
光学相干层析成像
深度学习
人工智能
卷积神经网络
回顾性队列研究
算法
数据集
地理萎缩
眼科
黄斑变性
内科学
计算机科学
作者
Eliot R. Dow,Hyeon Ki Jeong,Ella Arnon Katz,Cynthia A. Toth,Dong Wang,Terry Lee,David Kuo,Michael J. Allingham,Majda Hadziahmetovic,Priyatham S. Mettu,Stefanie Schuman,Lawrence Carin,Pearse A. Keane,Ricardo Henao,Eleonora M. Lad
出处
期刊:JAMA Ophthalmology
[American Medical Association]
日期:2023-10-19
卷期号:141 (11): 1052-1052
被引量:5
标识
DOI:10.1001/jamaophthalmol.2023.4659
摘要
The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans.
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