医学
人工智能
精密医学
机器学习
多样性(控制论)
疾病
大数据
数据科学
深度学习
计算机科学
病理
数据挖掘
作者
Li Lian Foo,Wei Yan Ng,Gilbert Yong San Lim,Tien‐En Tan,Marcus Ang,Daniel Shu Wei Ting
出处
期刊:Current Opinion in Ophthalmology
[Ovid Technologies (Wolters Kluwer)]
日期:2021-07-26
卷期号:32 (5): 413-424
被引量:21
标识
DOI:10.1097/icu.0000000000000791
摘要
Myopia is one of the leading causes of visual impairment, with a projected increase in prevalence globally. One potential approach to address myopia and its complications is early detection and treatment. However, current healthcare systems may not be able to cope with the growing burden. Digital technological solutions such as artificial intelligence (AI) have emerged as a potential adjunct for myopia management.There are currently four significant domains of AI in myopia, including machine learning (ML), deep learning (DL), genetics and natural language processing (NLP). ML has been demonstrated to be a useful adjunctive for myopia prediction and biometry for cataract surgery in highly myopic individuals. DL techniques, particularly convoluted neural networks, have been applied to various image-related diagnostic and predictive solutions. Applications of AI in genomics and NLP appear to be at a nascent stage.Current AI research is mainly focused on disease classification and prediction in myopia. Through greater collaborative research, we envision AI will play an increasingly critical role in big data analysis by aggregating a greater variety of parameters including genomics and environmental factors. This may enable the development of generalizable adjunctive DL systems that could help realize predictive and individualized precision medicine for myopic patients.
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