Artificial intelligence and machine learning in ophthalmology: A review

被引：33
作者：
Srivastava, Ojas [1 ]
Tennant, Matthew [2 ]
Grewal, Parampal [2 ,3 ]
Rubin, Uriel [2 ]
Seamone, Mark [2 ,4 ]
机构：
[1] Univ Alberta, Fac Med & Dent, Edmonton, AB, Canada
[2] Univ Alberta, Dept Ophthalmol & Visual Sci, Edmonton, AB, Canada
[3] Univ Toronto, Dept Ophthalmol & Vis Sci, Toronto, ON, Canada
[4] Alberta Retina Consultants Su 400, 10924 107 Ave, Edmonton, AB, Canada
来源：
INDIAN JOURNAL OF OPHTHALMOLOGY | 2023年 / 71卷 / 01期
基金：
英国科研创新办公室;
关键词：
AI; anterior segment; cornea; ophthalmology; retina; pediatrics; OPTICAL COHERENCE TOMOGRAPHY; DIABETIC-RETINOPATHY; MACULAR DEGENERATION; GLAUCOMA PROGRESSION; DEEP; IMAGES; VALIDATION; SEGMENTATION; NEUROPATHY; ALGORITHM;
D O I：
10.4103/ijo.IJO_1569_22
中图分类号：
R77 [眼科学];
学科分类号：
100212 ;
摘要：
Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implications on every subspecialty within medicine. This review highlights the applications of AI in ophthalmology: a specialty that lends itself well to the integration of computer algorithms due to the high volume of digital imaging, data, and objective metrics such as central retinal thickness. The focus of this review is the use of AI in retina, cornea, anterior segment, and pediatrics.
引用
收藏
页码：11 / 17
页数：7
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