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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Bibliografiske detaljer

Principais autores:	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:	Artigo
Sprog:	Inglês
Udgivet:	Elsevier 2023-09-01
Serier:	Ophthalmology Science
Fag:	Aging Biomarker discovery Deep learning Machine learning Retina
Online adgang:	http://www.sciencedirect.com/science/article/pii/S266691452300026X
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