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Assessing glaucoma in retinal fundus photographs using Deep Feature Consistent Variational Autoencoders


Oct 04, 2021
Sayan Mandal, Alessandro A. Jammal, Felipe A. Medeiros

* Corresponding author: Felipe A. Medeiros 

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RetiNerveNet: Using Recursive Deep Learning to Estimate Pointwise 24-2 Visual Field Data based on Retinal Structure


Oct 15, 2020
Shounak Datta, Eduardo B. Mariottoni, David Dov, Alessandro A. Jammal, Lawrence Carin, Felipe A. Medeiros


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Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in Glaucoma


Aug 24, 2019
Samuel I. Berchuck, Felipe A. Medeiros, Sayan Mukherjee

* This is a preprint of an article submitted for publication in the Annals of Applied Statistics. The article contains 26 pages and 7 figures 

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Deep Learning to Assess Glaucoma Risk and Associated Features in Fundus Images


Dec 21, 2018
Sonia Phene, R. Carter Dunn, Naama Hammel, Yun Liu, Jonathan Krause, Naho Kitade, Mike Schaekermann, Rory Sayres, Derek J. Wu, Ashish Bora, Christopher Semturs, Anita Misra, Abigail E. Huang, Arielle Spitze, Felipe A. Medeiros, April Y. Maa, Monica Gandhi, Greg S. Corrado, Lily Peng, Dale R. Webster


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From Machine to Machine: An OCT-trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs


Oct 20, 2018
Felipe A. Medeiros, Alessandro A. Jammal, Atalie C. Thompson


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