The Asia-Pacific Journal of Ophthalmology

Asia-Pacific Journal of Ophthalmology:

Issue 6, November/December 2018 Review Article

Can Artificial Intelligence Make Screening Faster, More Accurate, and More Accessible?

Li, Zhixi; Keel, Stuart; Liu, Chi; He, Mingguang



Author Information


From the *State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China; and †Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia.


Reprints: Mingguang He, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, 54 S Xianlie Road, Guangzhou 510060, China. 
E-mail: mingguang.he@unimelb.edu.au.



Abstract


Diabetic retinopathy, glaucoma, and age-related macular degeneration are leading causes of vision loss and blindness worldwide. They tend to be asymptomatic in the early phase of disease and therefore require active screening programs to identify the patients requiring referral and treatment. Deep learning–based artificial intelligence technology has recently become a major topic in the field of ophthalmology. This paper aimed to provide a general view of the major findings on the application of deep learning for the classification of eye diseases from common imaging modalities. In the future, it is expected that these technologies will be applied in real-world screening programs to improve their efficiency and affordability.




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