Deep-learning based automated quantification of critical optical coherence tomography features in neovascular age-related macular degeneration
Author:
Publisher
Springer Science and Business Media LLC
Subject
Ophthalmology
Link
https://www.nature.com/articles/s41433-023-02720-8.pdf
Reference27 articles.
1. Friedman DS, O’Colmain BJ, Muñoz B, Tomany SC, McCarty C, de Jong PTVM, et al. Prevalence of age-related macular degeneration in the United States. Arch Ophthalmol. 2004;122:564–72.
2. Spaide RF, Jaffe GJ, Sarraf D, Freund KB, Sadda SR, Staurenghi G, et al. Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data: Consensus on Neovascular Age-Related Macular Degeneration Nomenclature Study Group. Ophthalmology. 2020;127:616–36.
3. Ferris FL, Wilkinson CP, Bird A, Chakravarthy U, Chew E, Csaky K, et al. Clinical classification of age-related macular degeneration. Ophthalmology 2013;120:844–51.
4. Ferris FL, Fine SL, Hyman L. Age-Related Macular Degeneration and Blindness Due to Neovascular Maculopathy. Arch Ophthalmol. 1984;102:1640–2.
5. Kaiser PK, Wykoff CC, Singh RP, Khanani AM, Do DV, Patel H, et al. Retinal Fluid And Thickness As Measures of Disease Activity In Neovascular Age-Related Macular Degeneration. Retina. 2021;41:1579–86.
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