Work

Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs

Year: 2019

Type: article

Source: American Journal of Ophthalmology

DOI: 10.1016/j.ajo.2019.11.006

Authors: Alessandro A. Jammal, Atalie C. Thompson, Eduardo B. Mariottoni, Samuel I. Berchuck, Carla N. Urata, Tais Estrela, Susan M. Wakil, Vital P. Costa, Felipe A. Medeiros

Institutions: Duke University, Universidade Estadual de Campinas (UNICAMP), Duke Medical Center

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Merck, Bausch and Lomb, Merck KGaA, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Carl Zeiss Meditec AG, Heidelberg Engineering, National Institutes of Health, Alcon, Allergan, National Eye Institute

Awards: Deep learning to quantify glaucomatous damage on fundus photographs for teleophthalmology, G4571277646, The BCI (Brain Computer Interface) Glaucoma Study: Objective Home-Based Detection of Progressive Visual Function Loss in Glaucoma

OpenAlex ID: W2987092895

FWCI: 8.245

Cites: 42

Cited by: 114

Related to: 10