A Deep Learning Approach to Improve Retinal Structural Predictions and Aid Glaucoma Neuroprotective Clinical Trial Design

Christopher, M., Hoseini, P., Walker, E., Proudfoot, J. A., Bowd, C., Fazio, M. A., Girkin, C. A., De Moraes, C. G., Liebmann, J. M., Weinreb, R. N., Schwartzman, A., Zangwill, L. M., & Welsbie, D. S. (2023). A Deep Learning Approach to Improve Retinal Structural Predictions and Aid Glaucoma Neuroprotective Clinical Trial Design. Ophthalmology Glaucoma, 6(2), 147–159. https://doi.org/10.1016/j.ogla.2022.08.014
Authors:
Mark Christopher
Pourya Hoseini
Evan Walker
James A Proudfoot
Christopher Bowd
Massimo A Fazio
Christopher A Girkin
Carlos Gustavo De Moraes
Jeffrey M Liebmann
Robert N Weinreb
Armin Schwartzman
Linda M Zangwill
Derek S Welsbie
Affiliated Authors:
Carlos Gustavo De Moraes
Jeffrey M Liebmann
Subjects:
Deep Learning (MeSH)
Glaucoma (MeSH)
Author Keywords:
clinical trial
deep learning
glaucoma
machine learning
neuroprotection
Publication Type:
Article
Unique ID:
10.1016/j.ogla.2022.08.014
PMID:
Publication Date:
Data Source:
PubMed

Record Created: