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

被引：113

作者：

Hogarty, Daniel T. ^{[1
]}

Mackey, David A. ^{[1
,2
,3
]}

Hewitt, Alex W. ^{[1
,2
,3
]}

机构：

[1] Univ Melbourne, Royal Victorian Eye & Ear Hosp, Ctr Eye Res Australia, Melbourne, Vic, Australia

[2] Univ Western Australia, Ctr Vis Sci, Lions Eye Inst, Perth, WA, Australia

[3] Univ Tasmania, Menzies Inst Med Res, Hobart, Tas, Australia

来源：

CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY | 2019年 / 47卷 / 01期

关键词：

artificial intelligence; deep learning; diabetic retinopathy; machine learning; ophthalmology; MACHINE LEARNING CLASSIFIERS; COLLAGEN CROSS-LINKING; DIABETIC-RETINOPATHY; KERATOCONUS DETECTION; MACULAR DEGENERATION; AUTOMATED IDENTIFICATION; CORNEAL TOPOGRAPHY; NEURAL-NETWORK; DEEP; AGE;

D O I：

10.1111/ceo.13381

中图分类号：

R77 [眼科学];

学科分类号：

100212 ;

摘要：

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.

引用

页码：128 / 139

页数：12

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