Big Data and Artificial Intelligence in Ophthalmology: Where Are We Now?-Reference-Cited by-同舟云学术

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Big Data and Artificial Intelligence in Ophthalmology: Where Are We Now?

Published:2021-06 Issue:2 Volume:1 Page:100036
ISSN:2666-9145
Container-title:Ophthalmology Science
language:en
Short-container-title:Ophthalmology Science

Author:

Lee Cecilia S.,Brandt James D.,Lee Aaron Y.

Funder

National Institute on Aging

National Eye Institute

National Institutes of Health

Research to Prevent Blindness

U.S. Food and Drug Administration

Publisher

Elsevier BV

Subject

General Materials Science

Reference22 articles.

1. A (very) brief history of artificial intelligence;Buchanan;AIMag,2005

2. Methodological challenges of deep learning in optical coherence tomography for retinal diseases: a review;Yanagihara;Transl Vis Sci Technol,2020

3. AAO Taskforce on AI and AAO Medical Information Technology Committee. Big data requirements for artificial intelligence;Wang;Curr Opin Ophthalmol,2020

4. The 2016 American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) database: characteristics and methods;Chiang;Ophthalmology,2018

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3. Development of oculomics artificial intelligence for cardiovascular risk factors: A case study in fundus oculomics for HbA1c assessment and clinically relevant considerations for clinicians;Asia-Pacific Journal of Ophthalmology;2024-07

4. Machine Learning Methods Using Artificial Intelligence Deployed on Electronic Health Record Data for Identification and Referral of At-Risk Patients From Primary Care Physicians to Eye Care Specialists: Retrospective, Case-Controlled Study;JMIR AI;2024-03-12

5. The role of artificial intelligence in modern ophthalmology;Ophthalmology Reports;2024-03-09

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