Application of artificial intelligence in ophthalmology
Artificial intelligence is a general term that means to accomplish a task mainly by a computer, with the least human beings participation, and it is widely accepted as the invention of robots. With the development of this new technology, artificial intelligence has been one of the most influential i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Press of International Journal of Ophthalmology (IJO PRESS)
2018-09-01
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| Series: | International Journal of Ophthalmology |
| Subjects: | |
| Online Access: | http://www.ijo.cn/en_publish/2018/9/20180921.pdf |
| _version_ | 1818081333691285504 |
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| author | Xue-Li Du Wen-Bo Li Bo-Jie Hu |
| author_facet | Xue-Li Du Wen-Bo Li Bo-Jie Hu |
| author_sort | Xue-Li Du |
| collection | DOAJ |
| description | Artificial intelligence is a general term that means to accomplish a task mainly by a computer, with the least human beings participation, and it is widely accepted as the invention of robots. With the development of this new technology, artificial intelligence has been one of the most influential information technology revolutions. We searched these English-language studies relative to ophthalmology published on PubMed and Springer databases. The application of artificial intelligence in ophthalmology mainly concentrates on the diseases with a high incidence, such as diabetic retinopathy, age-related macular degeneration, glaucoma, retinopathy of prematurity, age-related or congenital cataract and few with retinal vein occlusion. According to the above studies, we conclude that the sensitivity of detection and accuracy for proliferative diabetic retinopathy ranged from 75% to 91.7%, for non-proliferative diabetic retinopathy ranged from 75% to 94.7%, for age-related macular degeneration it ranged from 75% to 100%, for retinopathy of prematurity ranged over 95%, for retinal vein occlusion just one study reported ranged over 97%, for glaucoma ranged 63.7% to 93.1%, and for cataract it achieved a more than 70% similarity against clinical grading. |
| first_indexed | 2024-12-10T19:04:33Z |
| format | Article |
| id | doaj.art-b8e6aabe9ebb497bad0b961c952e41bb |
| institution | Directory Open Access Journal |
| issn | 2222-3959 2227-4898 |
| language | English |
| last_indexed | 2024-12-10T19:04:33Z |
| publishDate | 2018-09-01 |
| publisher | Press of International Journal of Ophthalmology (IJO PRESS) |
| record_format | Article |
| series | International Journal of Ophthalmology |
| spelling | doaj.art-b8e6aabe9ebb497bad0b961c952e41bb2022-12-22T01:36:55ZengPress of International Journal of Ophthalmology (IJO PRESS)International Journal of Ophthalmology2222-39592227-48982018-09-011191555156110.18240/ijo.2018.09.21Application of artificial intelligence in ophthalmologyXue-Li Du0Wen-Bo Li1Bo-Jie Hu2Tianjin Medical University Eye Hospital, Tianjin 300384, ChinaTianjin Medical University Eye Hospital, Tianjin 300384, ChinaTianjin Medical University Eye Hospital, Tianjin 300384, ChinaArtificial intelligence is a general term that means to accomplish a task mainly by a computer, with the least human beings participation, and it is widely accepted as the invention of robots. With the development of this new technology, artificial intelligence has been one of the most influential information technology revolutions. We searched these English-language studies relative to ophthalmology published on PubMed and Springer databases. The application of artificial intelligence in ophthalmology mainly concentrates on the diseases with a high incidence, such as diabetic retinopathy, age-related macular degeneration, glaucoma, retinopathy of prematurity, age-related or congenital cataract and few with retinal vein occlusion. According to the above studies, we conclude that the sensitivity of detection and accuracy for proliferative diabetic retinopathy ranged from 75% to 91.7%, for non-proliferative diabetic retinopathy ranged from 75% to 94.7%, for age-related macular degeneration it ranged from 75% to 100%, for retinopathy of prematurity ranged over 95%, for retinal vein occlusion just one study reported ranged over 97%, for glaucoma ranged 63.7% to 93.1%, and for cataract it achieved a more than 70% similarity against clinical grading.http://www.ijo.cn/en_publish/2018/9/20180921.pdf1561artificial intelligencedeep learningmachine learningimages processingophthalmology |
| spellingShingle | Xue-Li Du Wen-Bo Li Bo-Jie Hu Application of artificial intelligence in ophthalmology International Journal of Ophthalmology 1561 artificial intelligence deep learning machine learning images processing ophthalmology |
| title | Application of artificial intelligence in ophthalmology |
| title_full | Application of artificial intelligence in ophthalmology |
| title_fullStr | Application of artificial intelligence in ophthalmology |
| title_full_unstemmed | Application of artificial intelligence in ophthalmology |
| title_short | Application of artificial intelligence in ophthalmology |
| title_sort | application of artificial intelligence in ophthalmology |
| topic | 1561 artificial intelligence deep learning machine learning images processing ophthalmology |
| url | http://www.ijo.cn/en_publish/2018/9/20180921.pdf |
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