학술논문
Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale
Document Type
Article
Author
Choi, Rene Y.; Brown, James M.; Kalpathy-Cramer, Jayashree; Chan, R. V. Paul; Ostmo, Susan; Chiang, Michael F.; Campbell, J. Peter; Chiang, Michael F.; Ostmo, Susan; Kim, Sang Jin; Sonmez, Kemal; Campbell, J. Peter; Chan, R. V. Paul; Jonas, Karyn; Horowitz, Jason; Coki, Osode; Eccles, Cheryl-Ann; Sarna, Leora; Orlin, Anton; Berrocal, Audina; Negron, Catherin; Denser, Kimberly; Cumming, Kristi; Osentoski, Tammy; Check, Tammy; Zajechowski, Mary; Lee, Thomas; Kruger, Evan; McGovern, Kathryn; Simmons, Charles; Murthy, Raghu; Galvis, Sharon; Rotter, Jerome; Chen, Ida; Li, Xiaohui; Taylor, Kent; Roll, Kaye; Kalpathy-Cramer, Jayashree; Erdogmus, Deniz; Ioannidis, Stratis; Martinez-Castellanos, Maria Ana; Salinas-Longoria, Samantha; Romero, Rafael; Arriola, Andrea; Olguin-Manriquez, Francisco; Meraz-Gutierrez, Miroslava; Dulanto-Reinoso, Carlos M.; Montero-Mendoza, Cristina
Source
Ophthalmology Retina; October 2020, Vol. 4 Issue: 10 p1016-1021, 6p
Subject
Language
ISSN
24687219; 24686530
Abstract
Retinopathy of prematurity is a leading cause of childhood blindness worldwide, but clinical diagnosis is subjective, which leads to treatment differences. Our goal was to determine objective differences in the diagnosis of plus disease between clinicians using an automated retinopathy of prematurity (ROP) vascular severity score.