Artificial intelligence and machine learning in ophthalmology: A review

Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implications on every subspecialty within medicine. This re...

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Detalles Bibliográficos
Autores principales: Srivastava, Ojas, Tennant, Matthew, Grewal, Parampal, Rubin, Uriel, Seamone, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2023
Materias:
Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155540/
https://www.ncbi.nlm.nih.gov/pubmed/36588202
http://dx.doi.org/10.4103/ijo.IJO_1569_22
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author Srivastava, Ojas
Tennant, Matthew
Grewal, Parampal
Rubin, Uriel
Seamone, Mark
author_facet Srivastava, Ojas
Tennant, Matthew
Grewal, Parampal
Rubin, Uriel
Seamone, Mark
author_sort Srivastava, Ojas
collection PubMed
description Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implications on every subspecialty within medicine. This review highlights the applications of AI in ophthalmology: a specialty that lends itself well to the integration of computer algorithms due to the high volume of digital imaging, data, and objective metrics such as central retinal thickness. The focus of this review is the use of AI in retina, cornea, anterior segment, and pediatrics.
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spelling pubmed-101555402023-05-04 Artificial intelligence and machine learning in ophthalmology: A review Srivastava, Ojas Tennant, Matthew Grewal, Parampal Rubin, Uriel Seamone, Mark Indian J Ophthalmol Review Article Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implications on every subspecialty within medicine. This review highlights the applications of AI in ophthalmology: a specialty that lends itself well to the integration of computer algorithms due to the high volume of digital imaging, data, and objective metrics such as central retinal thickness. The focus of this review is the use of AI in retina, cornea, anterior segment, and pediatrics. Wolters Kluwer - Medknow 2023-01 2022-12-30 /pmc/articles/PMC10155540/ /pubmed/36588202 http://dx.doi.org/10.4103/ijo.IJO_1569_22 Text en Copyright: © 2022 Indian Journal of Ophthalmology https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Review Article
Srivastava, Ojas
Tennant, Matthew
Grewal, Parampal
Rubin, Uriel
Seamone, Mark
Artificial intelligence and machine learning in ophthalmology: A review
title Artificial intelligence and machine learning in ophthalmology: A review
title_full Artificial intelligence and machine learning in ophthalmology: A review
title_fullStr Artificial intelligence and machine learning in ophthalmology: A review
title_full_unstemmed Artificial intelligence and machine learning in ophthalmology: A review
title_short Artificial intelligence and machine learning in ophthalmology: A review
title_sort artificial intelligence and machine learning in ophthalmology: a review
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155540/
https://www.ncbi.nlm.nih.gov/pubmed/36588202
http://dx.doi.org/10.4103/ijo.IJO_1569_22
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