Enhancing Self-Supervised Learning for Rare Diseases in OCT—Reply-Reference-Cited by-同舟云学术

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Enhancing Self-Supervised Learning for Rare Diseases in OCT—Reply

Published:2024-07-01 Issue:7 Volume:142 Page:688
ISSN:2168-6165
Container-title:JAMA Ophthalmology
language:en
Short-container-title:JAMA Ophthalmol

Author:

Gholami Shahrzad¹,Scheppke Lea²,Lee Aaron Y.³⁴

Affiliation:

1. AI for Good Lab, Microsoft Research, Redmond, Washington

2. Lowy Medical Research Institute, La Jolla, California

3. Department of Ophthalmology, University of Washington, Seattle

4. Roger and Angie Karalis Johnson Retina Center, Seattle, Washington

Publisher

American Medical Association (AMA)

Link

https://jamanetwork.com/journals/jamaophthalmology/articlepdf/2819803/jamaophthalmology_gholami_2024_lr_240008_1719935969.93707.pdf

Reference4 articles.

1. Self-supervised learning for improved optical coherence tomography detection of macular telangiectasia type 2.;Gholami;JAMA Ophthalmol,2024

2. The future of digital health with federated learning.;Rieke;NPJ Digit Med,2020

3. Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging.;Azizi;Nat Biomed Eng,2023

4. Bootstrap your own latent: a new approach to self-supervised learning.;Grill;Adv Neural Inf Process Syst,2020

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