Literature DB >> 30248307

The current state of artificial intelligence in ophthalmology.

Rahul Kapoor1, Stephen P Walters1, Lama A Al-Aswad2.   

Abstract

Artificial intelligence (AI) is a branch of computer science that deals with the development of algorithms that seek to simulate human intelligence. We provide an overview of the basic principles in AI that are essential to the understanding of AI and its application in health care. We also present a descriptive analysis of the current state of AI in various fields of medicine, especially ophthalmology. Finally, we review the potential limitations and challenges that come along with the development and implementation of this new technology that will likely play a major role in clinical medicine in the near future.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  artificial intelligence; convolutional neural network; deep learning; deep reinforcement learning; machine learning; natural language processing; neural network; ophthalmology; teleophthalmology

Mesh:

Year:  2018        PMID: 30248307     DOI: 10.1016/j.survophthal.2018.09.002

Source DB:  PubMed          Journal:  Surv Ophthalmol        ISSN: 0039-6257            Impact factor:   6.048


  19 in total

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2.  Protocol for a systematic review and meta-analysis of the diagnostic accuracy of artificial intelligence for grading of ophthalmology imaging modalities.

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Journal:  Telemed J E Health       Date:  2020-03-25       Impact factor: 3.536

4.  Evaluation of pediatric ophthalmologists' perspectives of artificial intelligence in ophthalmology.

Authors:  Nita G Valikodath; Tala Al-Khaled; Emily Cole; Daniel S W Ting; Elmer Y Tu; J Peter Campbell; Michael F Chiang; Joelle A Hallak; R V Paul Chan
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5.  The second information revolution: digitalization brings opportunities and concerns for public health.

Authors:  Martin McKee; May C I van Schalkwyk; David Stuckler
Journal:  Eur J Public Health       Date:  2019-10-01       Impact factor: 3.367

Review 6.  Telemedicine for Retinopathy of Prematurity.

Authors:  Christopher J Brady; Samantha D'Amico; J Peter Campbell
Journal:  Telemed J E Health       Date:  2020-03-25       Impact factor: 3.536

7.  Detection of Fuchs' Uveitis Syndrome From Slit-Lamp Images Using Deep Convolutional Neural Networks in a Chinese Population.

Authors:  Wanyun Zhang; Zhijun Chen; Han Zhang; Guannan Su; Rui Chang; Lin Chen; Ying Zhu; Qingfeng Cao; Chunjiang Zhou; Yao Wang; Peizeng Yang
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8.  Performance of Classification Systems for Age-Related Macular Degeneration in the Rotterdam Study.

Authors:  Eric F Thee; Magda A Meester-Smoor; Daniel T Luttikhuizen; Johanna M Colijn; Clair A Enthoven; Annechien E G Haarman; Dimitris Rizopoulos; Caroline C W Klaver
Journal:  Transl Vis Sci Technol       Date:  2020-04-24       Impact factor: 3.283

9.  Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.

Authors:  Bhavana Sosale; Aravind R Sosale; Hemanth Murthy; Sabyasachi Sengupta; Muralidhar Naveenam
Journal:  Indian J Ophthalmol       Date:  2020-02       Impact factor: 1.848

10.  Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.

Authors:  Anna S Mursch-Edlmayr; Wai Siene Ng; Alberto Diniz-Filho; David C Sousa; Louis Arnold; Matthew B Schlenker; Karla Duenas-Angeles; Pearse A Keane; Jonathan G Crowston; Hari Jayaram
Journal:  Transl Vis Sci Technol       Date:  2020-10-15       Impact factor: 3.283

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