eCite Digital Repository

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

Citation

Hogarty, DT and Mackey, DA and Hewitt, AW, Current state and future prospects of artificial intelligence in ophthalmology: a review, Clinical and Experimental Ophthalmology, 47, (1) pp. 128-139. ISSN 1442-6404 (2018) [Refereed Article]


Preview
PDF
864Kb
  

Copyright Statement

Copyright 2018 Royal Australian and New Zealand College of Ophthalmologists. This is the peer reviewed version of the following article: Current state and future prospects of artificial intelligence in ophthalmology: a review, which has been published in final form at http://dx.doi.org/10.1111/ceo.13381. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

DOI: doi:10.1111/ceo.13381

Abstract

Artificial intelligence (AI) has emerged as a major frontier in computer science research. Although AI has broad application across many medical fields, it will have particular utility in ophthalmology and will dramatically change the diagnostic and treatment pathways for many eye conditions such as corneal ectasias, glaucoma, age-related macular degeneration and diabetic retinopathy. However, given that AI has primarily been driven as a computer science, its concepts and terminology are unfamiliar to many medical professionals. Important key terms such as machine learning and deep learning are often misunderstood and incorrectly used interchangeably. This article presents an overview of AI and new developments relevant to ophthalmology.

Item Details

Item Type:Refereed Article
Keywords:artificial intelligence, deep learning, machine learning, ophthalmology, diabetic retinopathy
Research Division:Medical and Health Sciences
Research Group:Ophthalmology and Optometry
Research Field:Ophthalmology
Objective Division:Health
Objective Group:Clinical Health (Organs, Diseases and Abnormal Conditions)
Objective Field:Hearing, Vision, Speech and Their Disorders
UTAS Author:Mackey, DA (Professor David Mackey)
UTAS Author:Hewitt, AW (Professor Alex Hewitt)
ID Code:128125
Year Published:2018
Web of Science® Times Cited:5
Deposited By:Menzies Institute for Medical Research
Deposited On:2018-09-04
Last Modified:2019-03-20
Downloads:2 View Download Statistics

Repository Staff Only: item control page