A Bayesian Hierarchical Spatial Longitudinal Model Improves Estimation of Local Macular Rates of Change in Glaucomatous Eyes-Reference-Cited by-同舟云学术

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A Bayesian Hierarchical Spatial Longitudinal Model Improves Estimation of Local Macular Rates of Change in Glaucomatous Eyes

Published:2024-01-29 Issue:1 Volume:13 Page:26
ISSN:2164-2591
Container-title:Translational Vision Science & Technology
language:en
Short-container-title:Trans. Vis. Sci. Tech.

Author:

Su Erica¹,Mohammadzadeh Vahid²,Mohammadi Massood²,Shi Lynn²,Law Simon K.²,Coleman Anne L.²,Caprioli Joseph²,Weiss Robert E.¹,Nouri-Mahdavi Kouros²

Affiliation:

1. Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA

2. Glaucoma Division, Stein Eye Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Reference32 articles.

1. A review of deep learning for screening, diagnosis, and detection of glaucoma progression;Thompson;Transl Vis Sci Technol,2020

2. Longitudinal modeling of glaucoma progression using 2-dimensional continuous-time hidden Markov model;Liu;Med Image Comput Comput Assist Interv,2013

3. A framework for assessing glaucoma progression using structural and functional indices jointly;Abu;PLoS One,2020

4. Ganglion cell complex: the optimal measure for detection of structural progression in the macula;Mohammadzadeh;Am J Ophthalmol,2022

5. The Ocular Hypertension Treatment Study: a randomized trial determines that topical ocular hypotensive medication delays or prevents the onset of primary open-angle glaucoma;Kass;Arch Ophthalmol,2002

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