Foveal Therapy in Blue Cone Monochromacy: Predictions of Visual Potential From Artificial Intelligence.
chromatic perimetry
cones
machine learning
optical coherence tomography
random forest
retinal degeneration
rods
visual acuity
Journal
Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481
Informations de publication
Date de publication:
2020
2020
Historique:
received:
25
03
2020
accepted:
07
07
2020
entrez:
28
8
2020
pubmed:
28
8
2020
medline:
28
8
2020
Statut:
epublish
Résumé
Novel therapeutic approaches for treating inherited retinal degenerations (IRDs) prompt a need to understand which patients with impaired vision have the anatomical potential to gain from participation in a clinical trial. We used supervised machine learning to predict foveal function from foveal structure in blue cone monochromacy (BCM), an X-linked congenital cone photoreceptor dysfunction secondary to mutations in the
Identifiants
pubmed: 32848570
doi: 10.3389/fnins.2020.00800
pmc: PMC7416698
doi:
Types de publication
Journal Article
Langues
eng
Pagination
800Informations de copyright
Copyright © 2020 Sumaroka, Cideciyan, Sheplock, Wu, Kohl, Wissinger and Jacobson.
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