Current state and future prospects of artificial intelligence in ophthalmology: a review-Reference-Cited by-同舟云学术

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Current state and future prospects of artificial intelligence in ophthalmology: a review

Published:2018-09-30 Issue:1 Volume:47 Page:128-139
ISSN:1442-6404
Container-title:Clinical & Experimental Ophthalmology
language:en
Short-container-title:Clin. Experiment. Ophthalmol.

Author:

Hogarty Daniel T¹^ORCID,Mackey David A¹²³,Hewitt Alex W¹²³

Affiliation:

1. Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne; Melbourne Victoria Australia

2. Lions Eye Institute, Centre for Vision Sciences, University of Western Australia; Perth Western Australia Australia

3. Menzies Institute for Medical Research, University of Tasmania; Hobart Tasmania Australia

Publisher

Wiley

Subject

Ophthalmology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/ceo.13381/fullpdf

Reference75 articles.

1. Deep learning applications in ophthalmology;Rahimy;Curr Opin Ophthalmol,2018

2. Strategies for training large scale neural network language models

3. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs;Gulshan;JAMA,2016

4. Bordes A Chopra S Weston J 2014 http://arxiv.org/abs/1406.3676

5. Some studies in machine learning using the game of checkers;Samuel;IBM J Res Dev,2000

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