Application of artificial intelligence in cataract management: current and future directions
Abstract The rise of artificial intelligence (AI) has brought breakthroughs in many areas of medicine. In ophthalmology, AI has delivered robust results in the screening and detection of diabetic retinopathy, age-related macular degeneration, glaucoma, and retinopathy of prematurity. Cataract manage...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-01-01
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| Series: | Eye and Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40662-021-00273-z |
| _version_ | 1798033427672334336 |
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| author | Laura Gutierrez Jane Sujuan Lim Li Lian Foo Wei Yan Yan Ng Michelle Yip Gilbert Yong San Lim Melissa Hsing Yi Wong Allan Fong Mohamad Rosman Jodhbir Singth Mehta Haotian Lin Darren Shu Jeng Ting Daniel Shu Wei Ting |
| author_facet | Laura Gutierrez Jane Sujuan Lim Li Lian Foo Wei Yan Yan Ng Michelle Yip Gilbert Yong San Lim Melissa Hsing Yi Wong Allan Fong Mohamad Rosman Jodhbir Singth Mehta Haotian Lin Darren Shu Jeng Ting Daniel Shu Wei Ting |
| author_sort | Laura Gutierrez |
| collection | DOAJ |
| description | Abstract The rise of artificial intelligence (AI) has brought breakthroughs in many areas of medicine. In ophthalmology, AI has delivered robust results in the screening and detection of diabetic retinopathy, age-related macular degeneration, glaucoma, and retinopathy of prematurity. Cataract management is another field that can benefit from greater AI application. Cataract is the leading cause of reversible visual impairment with a rising global clinical burden. Improved diagnosis, monitoring, and surgical management are necessary to address this challenge. In addition, patients in large developing countries often suffer from limited access to tertiary care, a problem further exacerbated by the ongoing COVID-19 pandemic. AI on the other hand, can help transform cataract management by improving automation, efficacy and overcoming geographical barriers. First, AI can be applied as a telediagnostic platform to screen and diagnose patients with cataract using slit-lamp and fundus photographs. This utilizes a deep-learning, convolutional neural network (CNN) to detect and classify referable cataracts appropriately. Second, some of the latest intraocular lens formulas have used AI to enhance prediction accuracy, achieving superior postoperative refractive results compared to traditional formulas. Third, AI can be used to augment cataract surgical skill training by identifying different phases of cataract surgery on video and to optimize operating theater workflows by accurately predicting the duration of surgical procedures. Fourth, some AI CNN models are able to effectively predict the progression of posterior capsule opacification and eventual need for YAG laser capsulotomy. These advances in AI could transform cataract management and enable delivery of efficient ophthalmic services. The key challenges include ethical management of data, ensuring data security and privacy, demonstrating clinically acceptable performance, improving the generalizability of AI models across heterogeneous populations, and improving the trust of end-users. |
| first_indexed | 2024-04-11T20:30:19Z |
| format | Article |
| id | doaj.art-5919de36414341e6af2c6d6811098be9 |
| institution | Directory Open Access Journal |
| issn | 2326-0254 |
| language | English |
| last_indexed | 2024-04-11T20:30:19Z |
| publishDate | 2022-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Eye and Vision |
| spelling | doaj.art-5919de36414341e6af2c6d6811098be92022-12-22T04:04:32ZengBMCEye and Vision2326-02542022-01-019111110.1186/s40662-021-00273-zApplication of artificial intelligence in cataract management: current and future directionsLaura Gutierrez0Jane Sujuan Lim1Li Lian Foo2Wei Yan Yan Ng3Michelle Yip4Gilbert Yong San Lim5Melissa Hsing Yi Wong6Allan Fong7Mohamad Rosman8Jodhbir Singth Mehta9Haotian Lin10Darren Shu Jeng Ting11Daniel Shu Wei Ting12Singapore Eye Research InstituteSingapore Eye Research InstituteSingapore Eye Research InstituteSingapore Eye Research InstituteSingapore Eye Research InstituteSingapore Eye Research InstituteSingapore National Eye CenterSingapore National Eye CenterSingapore Eye Research InstituteSingapore Eye Research InstituteZhongshan Ophthalmic Center, Sun Yet Sen UniversityAcademic Ophthalmology, School of Medicine, University of NottinghamSingapore Eye Research InstituteAbstract The rise of artificial intelligence (AI) has brought breakthroughs in many areas of medicine. In ophthalmology, AI has delivered robust results in the screening and detection of diabetic retinopathy, age-related macular degeneration, glaucoma, and retinopathy of prematurity. Cataract management is another field that can benefit from greater AI application. Cataract is the leading cause of reversible visual impairment with a rising global clinical burden. Improved diagnosis, monitoring, and surgical management are necessary to address this challenge. In addition, patients in large developing countries often suffer from limited access to tertiary care, a problem further exacerbated by the ongoing COVID-19 pandemic. AI on the other hand, can help transform cataract management by improving automation, efficacy and overcoming geographical barriers. First, AI can be applied as a telediagnostic platform to screen and diagnose patients with cataract using slit-lamp and fundus photographs. This utilizes a deep-learning, convolutional neural network (CNN) to detect and classify referable cataracts appropriately. Second, some of the latest intraocular lens formulas have used AI to enhance prediction accuracy, achieving superior postoperative refractive results compared to traditional formulas. Third, AI can be used to augment cataract surgical skill training by identifying different phases of cataract surgery on video and to optimize operating theater workflows by accurately predicting the duration of surgical procedures. Fourth, some AI CNN models are able to effectively predict the progression of posterior capsule opacification and eventual need for YAG laser capsulotomy. These advances in AI could transform cataract management and enable delivery of efficient ophthalmic services. The key challenges include ethical management of data, ensuring data security and privacy, demonstrating clinically acceptable performance, improving the generalizability of AI models across heterogeneous populations, and improving the trust of end-users.https://doi.org/10.1186/s40662-021-00273-zArtificial intelligenceTelemedicineCataractCataract screeningCataract surgeryIOL calculations |
| spellingShingle | Laura Gutierrez Jane Sujuan Lim Li Lian Foo Wei Yan Yan Ng Michelle Yip Gilbert Yong San Lim Melissa Hsing Yi Wong Allan Fong Mohamad Rosman Jodhbir Singth Mehta Haotian Lin Darren Shu Jeng Ting Daniel Shu Wei Ting Application of artificial intelligence in cataract management: current and future directions Eye and Vision Artificial intelligence Telemedicine Cataract Cataract screening Cataract surgery IOL calculations |
| title | Application of artificial intelligence in cataract management: current and future directions |
| title_full | Application of artificial intelligence in cataract management: current and future directions |
| title_fullStr | Application of artificial intelligence in cataract management: current and future directions |
| title_full_unstemmed | Application of artificial intelligence in cataract management: current and future directions |
| title_short | Application of artificial intelligence in cataract management: current and future directions |
| title_sort | application of artificial intelligence in cataract management current and future directions |
| topic | Artificial intelligence Telemedicine Cataract Cataract screening Cataract surgery IOL calculations |
| url | https://doi.org/10.1186/s40662-021-00273-z |
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