Cardiovascular Risk Prediction based on Retinal Vessel Analysis using Machine Learning

被引：0

作者：

Fathalla, Karma M. ^{[1
,2
]}

Ekart, Aniko ^{[2
]}

Seshadri, Swathi ^{[3
]}

Gherghe, Doina ^{[3
]}

机构：

[1] Arab Acad Sci & Tehnol, Comp Engn Dept, Alexandria, Egypt

[2] Aston Univ, ALICE, Birmingham, W Midlands, England

[3] Aston Univ, Vasc Res Lab, Birmingham, W Midlands, England

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2016年

关键词：

DIAMETER;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Cardiovascular risk prediction is a vital aspect of personalized health care. In this study, retinal vascular function is assessed in asymptomatic participants who are classified into risk groups based on Framingham Risk Score. Feature selection, oversampling and state-of-the-art classification methods are applied to provide a sound individual risk prediction based on Retinal Vessel Analysis (RVA) data obtained by non-invasive methods. The results indicate that the RVA based cardiovascular risk prediction models are competitive with well established Framingham and Qrisk based models.

引用

页码：880 / 885

页数：6

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