Artificial intelligence for diabetic retinopathy

被引:9
|
作者
Li, Sicong [1 ,2 ]
Zhao, Ruiwei [3 ]
Zou, Haidong [1 ,2 ,4 ,5 ,6 ]
机构
[1] Shanghai Jiao Tong Univ, Shanghai Peoples Hosp 1, Sch Med, Dept Ophthalmol,Shanghai Gen Hosp, Shanghai 200080, Peoples R China
[2] Shanghai Eye Hosp, Shanghai Eye Dis Prevent & Treatment Ctr, Shanghai 200040, Peoples R China
[3] Fudan Univ, Shanghai, Peoples R China
[4] Shanghai Key Lab Fundus Dis, Shanghai 200080, Peoples R China
[5] Natl Clin Res Ctr Eye Dis, Shanghai 200080, Peoples R China
[6] Shanghal Engn Ctr Precise Diag & Treatment Eye Di, Shanghai 200080, Peoples R China
关键词
Artificial intelligence; Deep learning; Diabetic retinopathy; MAJOR RISK-FACTORS; AUTOMATED DETECTION; GLOBAL PREVALENCE; SCREENING-PROGRAM; RETINAL IMAGES; VALIDATION; TELEMEDICINE; GUIDELINES; ADHERENCE; PATTERNS;
D O I
10.1097/CM9.0000000000001816
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Diabetic retinopathy (DR) is an important cause of blindness globally, and its prevalence is increasing. Early detection and intervention can help change the outcomes of the disease. The rapid development of artificial intelligence (AI) in recent years has led to new possibilities for the screening and diagnosis of DR. An AI-based diagnostic system for the detection of DR has significant advantages, such as high efficiency, high accuracy, and lower demand for human resources. At the same time, there are shortcomings, such as the lack of standards for development and evaluation and the limited scope of application. This article demonstrates the current applications of AI in the field of DR, existing problems, and possible future development directions.
引用
收藏
页码:253 / 260
页数:8
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