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Preventing corneal blindness caused by keratitis using artificial intelligence
Keratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of ophthalmologists, especially in resource-limited set...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213803/ https://www.ncbi.nlm.nih.gov/pubmed/34145294 http://dx.doi.org/10.1038/s41467-021-24116-6 |
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author | Li, Zhongwen Jiang, Jiewei Chen, Kuan Chen, Qianqian Zheng, Qinxiang Liu, Xiaotian Weng, Hongfei Wu, Shanjun Chen, Wei |
author_facet | Li, Zhongwen Jiang, Jiewei Chen, Kuan Chen, Qianqian Zheng, Qinxiang Liu, Xiaotian Weng, Hongfei Wu, Shanjun Chen, Wei |
author_sort | Li, Zhongwen |
collection | PubMed |
description | Keratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of ophthalmologists, especially in resource-limited settings, making the early diagnosis of keratitis challenging. Here, we develop a deep learning system for the automated classification of keratitis, other cornea abnormalities, and normal cornea based on 6,567 slit-lamp images. Our system exhibits remarkable performance in cornea images captured by the different types of digital slit lamp cameras and a smartphone with the super macro mode (all AUCs>0.96). The comparable sensitivity and specificity in keratitis detection are observed between the system and experienced cornea specialists. Our system has the potential to be applied to both digital slit lamp cameras and smartphones to promote the early diagnosis and treatment of keratitis, preventing the corneal blindness caused by keratitis. |
format | Online Article Text |
id | pubmed-8213803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82138032021-07-01 Preventing corneal blindness caused by keratitis using artificial intelligence Li, Zhongwen Jiang, Jiewei Chen, Kuan Chen, Qianqian Zheng, Qinxiang Liu, Xiaotian Weng, Hongfei Wu, Shanjun Chen, Wei Nat Commun Article Keratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of ophthalmologists, especially in resource-limited settings, making the early diagnosis of keratitis challenging. Here, we develop a deep learning system for the automated classification of keratitis, other cornea abnormalities, and normal cornea based on 6,567 slit-lamp images. Our system exhibits remarkable performance in cornea images captured by the different types of digital slit lamp cameras and a smartphone with the super macro mode (all AUCs>0.96). The comparable sensitivity and specificity in keratitis detection are observed between the system and experienced cornea specialists. Our system has the potential to be applied to both digital slit lamp cameras and smartphones to promote the early diagnosis and treatment of keratitis, preventing the corneal blindness caused by keratitis. Nature Publishing Group UK 2021-06-18 /pmc/articles/PMC8213803/ /pubmed/34145294 http://dx.doi.org/10.1038/s41467-021-24116-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Li, Zhongwen Jiang, Jiewei Chen, Kuan Chen, Qianqian Zheng, Qinxiang Liu, Xiaotian Weng, Hongfei Wu, Shanjun Chen, Wei Preventing corneal blindness caused by keratitis using artificial intelligence |
title | Preventing corneal blindness caused by keratitis using artificial intelligence |
title_full | Preventing corneal blindness caused by keratitis using artificial intelligence |
title_fullStr | Preventing corneal blindness caused by keratitis using artificial intelligence |
title_full_unstemmed | Preventing corneal blindness caused by keratitis using artificial intelligence |
title_short | Preventing corneal blindness caused by keratitis using artificial intelligence |
title_sort | preventing corneal blindness caused by keratitis using artificial intelligence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213803/ https://www.ncbi.nlm.nih.gov/pubmed/34145294 http://dx.doi.org/10.1038/s41467-021-24116-6 |
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