Forecasting future Humphrey Visual Fields using deep learning.

Journal: PloS one

Published Date: Apr 5, 2019

PURPOSE: To determine if deep learning networks could be trained to forecast future 24-2 Humphrey Visual Fields (HVFs).

Joanne C Wen

Department of Ophthalmology, University of Washington, Seattle, WA, United States of America.
Cecilia S Lee

Department of Ophthalmology, University of Washington, Seattle, Washington, USA.
Pearse A Keane

National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
Sa Xiao

Department of Ophthalmology, University of Washington, Seattle, Washington, USA.
Ariel S Rokem

eScience Institute, University of Washington, Seattle, WA, United States of America.
Philip P Chen

Department of Ophthalmology, University of Washington, Seattle, WA, United States of America.
Yue Wu

Key Laboratory of Luminescence and Real-Time Analytical Chemistry (Ministry of Education), College of Pharmaceutical Sciences, Southwest University, Chongqing 400716, China.
Aaron Y Lee

Department of Ophthalmology, University of Washington, Seattle, Washington.

Adult Aged Algorithms Databases, Factual Deep Learning Disease Progression Female Forecasting Glaucoma Humans Linear Models Male Middle Aged Models, Statistical Spatio-Temporal Analysis Visual Field Tests Visual Fields

View on PubMed Access via DOI PubMed (30951547)