Clinical evaluation of deep learning systems for assisting in the diagnosis of the epiretinal membrane grade in general ophthalmologists
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Ophthalmology
Link
https://www.nature.com/articles/s41433-023-02765-9.pdf
Reference28 articles.
1. Bu S-C, Kuijer R, Li X-R, Hooymans JMM, Los LI. Idiopathic epiretinal membrane. Retina. 2014;34:2317–35.
2. Meuer SM, Myers CE, Klein BEK, Swift MK, Huang Y, Gangaputra S, et al. The epidemiology of vitreoretinal interface abnormalities as detected by spectral-domain optical coherence tomography: the beaver dam eye study. Ophthalmology. 2015;122:787–95.
3. Fung AT, Galvin J, Tran T. Epiretinal membrane: a review. Clin Exp Ophthalmol. 2021;49:289–308.
4. Delyfer M-N, Legout P, Le Goff M, Blaizeau M, Rougier M-B, Schweitzer C, et al. Prevalence of epiretinal membranes in the ageing population using retinal colour images and SD-OCT: the Alienor sudy. Acta ophthalmol. 2020;98:e830–8.
5. Hwang J-U, Sohn J, Moon BG, Joe SG, Lee JY, Kim J-G, et al. Assessment of macular function for idiopathic epiretinal membranes classified by spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2012;53:3562–9.
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