Development and Validation of a Deep Learning System for Diagnosing Glaucoma Using Optical Coherence Tomography

This study aimed to develop and validate a deep learning system for diagnosing glaucoma using optical coherence tomography (OCT). A training set of 1822 eyes (332 control, 1490 glaucoma) with 7288 OCT images, an internal validation set of 425 eyes (104 control, 321 glaucoma) with 1700 images, and an...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Ko Eun, Kim, Joon Mo, Song, Ji Eun, Kee, Changwon, Han, Jong Chul, Hyun, Seung Hyup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408821/
https://www.ncbi.nlm.nih.gov/pubmed/32659918
http://dx.doi.org/10.3390/jcm9072167

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408821/
https://www.ncbi.nlm.nih.gov/pubmed/32659918
http://dx.doi.org/10.3390/jcm9072167

Ejemplares similares