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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]
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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.
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: | 9 |
| Deposited By: | Menzies Institute for Medical Research |
| Deposited On: | 2018-09-04 |
| Last Modified: | 2019-12-03 |
| Downloads: | 71 View Download Statistics |
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