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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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Autori principali: 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
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2023-09-01
Serie:Ophthalmology Science
Soggetti:
Aging
Biomarker discovery
Deep learning
Machine learning
Retina
Accesso online:http://www.sciencedirect.com/science/article/pii/S266691452300026X
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