眼视光学杂志(英文版)2024,Vol.10Issue(1) :21-30.DOI:10.1186/s40662-021-00273-z

jApplication of artificial intelligence in cataract management:current and future directions

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
眼视光学杂志(英文版)2024,Vol.10Issue(1) :21-30.DOI:10.1186/s40662-021-00273-z

jApplication of artificial intelligence in cataract management:current and future directions

Laura Gutierrez 1Jane Sujuan Lim 2Li Lian Foo 2Wei Yan Yan Ng 2Michelle Yip 2Gilbert Yong San Lim 1Melissa Hsing Yi Wong 3Allan Fong 3Mohamad Rosman 2Jodhbir Singth Mehta 2Haotian Lin 4Darren Shu Jeng Ting 5Daniel Shu Wei Ting2
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作者信息

  • 1. Singapore Eye Research Institute,Singapore,Singapore
  • 2. Singapore Eye Research Institute,Singapore,Singapore;Singapore National Eye Center,11 Third Hospital Avenue,Singapore 168751,Singapore
  • 3. Singapore National Eye Center,11 Third Hospital Avenue,Singapore 168751,Singapore
  • 4. Zhongshan Ophthalmic Center,Sun Yet Sen University,Guangzhou,China
  • 5. Academic Ophthalmology,School of Medicine,University of Nottingham,Nottingham,UK
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Abstract

The rise of artificial intelligence(AI)has brought breakthroughs in many areas of medicine.In ophthalmology,Al has delivered robust results in the screening and detection of diabetic retinopathy,age-related macular degenera-tion,glaucoma,and retinopathy of prematurity.Cataract management is another field that can benefit from greater Al 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.Al on the other hand,can help transform cataract management by improving automation,efficacy and overcoming geographical barriers.First,Al 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 Al to enhance prediction accuracy,achieving superior postoperative refractive results compared to traditional formulas.Third,Al 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 Al CNN models are able to effectively predict the progression of posterior capsule opacification and eventual need for yttrium aluminum garnet(YAG)laser capsulotomy.These advances in Al 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 Al models across heterogeneous populations,and improving the trust of end-users.

Key words

Artificial intelligence/Telemedicine/Cataract/Cataract screening/Cataract surgery/IOL calculations/Biometry/Machine learning

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出版年

2024
眼视光学杂志(英文版)

眼视光学杂志(英文版)

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