Retinal image-based artificial intelligence in detecting and predicting kidney diseases: Current advances and future perspectives

被引:5
|
作者
Wen, Jingyi [1 ]
Liu, Dong [1 ]
Wu, Qianni [1 ]
Zhao, Lanqin [1 ]
Iao, Wai Cheng [1 ]
Lin, Haotian [1 ,2 ,3 ,4 ]
机构
[1] Sun Yat sen Univ, Zhongshan Ophthalm Ctr, Guangdong Prov Clin Res Ctr Ocular Dis, State Key Lab Ophthalmol, Guangzhou, Peoples R China
[2] Sun Yat Sen Univ, Ctr Precis Med, Guangzhou, Peoples R China
[3] Sun Yat Sen Univ, Zhongshan Sch Med, Dept Genet & Biomed Informat, Guangzhou, Peoples R China
[4] Sun Yat Sen Univ, Zhongshan Ophthalm Ctr, Xian Lie South Rd 54, Guangzhou 510060, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
artificial intelligence; deep learning; fundus image; kidney diseases; diagnosis; prognosis and prediction; DEEP LEARNING-SYSTEM; DIABETIC-RETINOPATHY; MICROVASCULAR ABNORMALITIES; BLOOD-FLOW; CHOROIDAL THICKNESS; VESSEL DIAMETERS; RISK-FACTORS; HEMODIALYSIS; MECHANISMS; POPULATION;
D O I
10.1002/VIW.20220070
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Artificial intelligence (AI) has reformed the healthcare system with its compelling capabilities of processing biomedical data for disease diagnosis, prediction, and individualized management. The eye, as a non-invasive observation window for many systemic diseases, can be used to detect the signs of chronic kidney diseases, and other diseases like hypertension and type 2 diabetes mellitus, based on specific manifestations of retinal images. Recent advances using AI technology have posed a great potential of using retinal images for rapid mass screening and prognosis prediction of kidney diseases. Herein, we outlined the key applications of AI in ophthalmology and the detection of systemic diseases based on retinal imaging, especially the current progress of retinal image-based AI models for the detection and prediction of kidney diseases. We hope to shed light on the current opportunities and future challenges in this field to provide suggestions for further improvement and applications.
引用
收藏
页数:19
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