Exploring Healthy Retinal Aging with Deep Learning

Exploring Healthy Retinal Aging with Deep Learning

Purpose: To study the individual course of retinal changes caused by healthy aging using deep learning. Design: Retrospective analysis of a large data set of retinal OCT images. Participants: A total of 85 709 adults between the age of 40 and 75 years of whom OCT images were acquired in the scope of...

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Main Authors: Martin J. Menten, PhD, Robbie Holland, MSc, Oliver Leingang, PhD, Hrvoje Bogunović, PhD, Ahmed M. Hagag, MD, Rebecca Kaye, MD, Sophie Riedl, MD, Ghislaine L. Traber, MD, Osama N. Hassan, MSc, Nick Pawlowski, PhD, Ben Glocker, PhD, Lars G. Fritsche, PhD, Hendrik P.N. Scholl, MD, Sobha Sivaprasad, MD, Ursula Schmidt-Erfurth, MD, Daniel Rueckert, PhD, Andrew J. Lotery, MD
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Ophthalmology Science
Subjects:
Aging
Biomarker discovery
Deep learning
Machine learning
Retina
Online Access:http://www.sciencedirect.com/science/article/pii/S266691452300026X

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http://www.sciencedirect.com/science/article/pii/S266691452300026X

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