Article

Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder

2019-05-30

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Purpose</h4> To develop a novel deep learning algorithm to improve estimation of rates of progression and prediction of future patterns of visual field loss in glaucoma. <h4>Design</h4> Prospective observational cohort. <h4>Methods</h4> A variational auto-encoder (VAE) was trained to learn a low-dimensional feature representation of standard automated perimetry (SAP) visual fields using 2...

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Literature Corpus work: a95d51c4-344e-582c-af98-fd0d663babd0
DOI: 10.1101/652487

Open publication

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