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

共 50 条

[41] Cardiovascular Disease Risk Prediction with Supervised Machine Learning Techniques
Dritsas, Elias
Alexiou, Sotiris
Moustakas, Konstantinos
ICT4AWE: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES FOR AGEING WELL AND E-HEALTH, 2022, : 315 - 321
[42] Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches
Gautam, Nitesh
Mueller, Joshua
Alqaisi, Omar
Gandhi, Tanmay
Malkawi, Abdallah
Tarun, Tushar
Alturkmani, Hani J.
Zulqarnain, Muhammed Ali
Pontone, Gianluca
Al'Aref, Subhi J.
CURRENT ATHEROSCLEROSIS REPORTS, 2023, 25 (12) : 1069 - 1081
[43] Machine learning in precision diabetes care and cardiovascular risk prediction
Evangelos K. Oikonomou
Rohan Khera
Cardiovascular Diabetology, 22
[44] An evolutionary machine learning algorithm for cardiovascular disease risk prediction
Ordikhani, Mohammad
Abadeh, Mohammad Saniee
Prugger, Christof
Hassannejad, Razieh
Mohammadifard, Noushin
Sarrafzadegan, Nizal
PLOS ONE, 2022, 17 (07):
[45] Prediction of Cardiovascular Diseases with Retinal Images Using Deep Learning
Vineetha, Tumu
Reddy, Danda Rami
Mahendra, Kandimalla
Lakshmi, Ballanki Dhana
2024 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND APPLIED INFORMATICS, ACCAI 2024, 2024,
[46] Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors
Cheng, Chien-Hsiang
Lee, Bor-Jen
Nfor, Oswald Ndi
Hsiao, Chih-Hsuan
Huang, Yi-Chia
Liaw, Yung-Po
BMC MEDICAL INFORMATICS AND DECISION MAKING, 2024, 24 (01)
[47] Machine learning based prediction models for cardiovascular disease risk using electronic health records data: systematic review and meta-analysis
Liu, Tianyi
Krentz, Andrew
Lu, Lei
Curcin, Vasa
EUROPEAN HEART JOURNAL - DIGITAL HEALTH, 2024, 6 (01): : 7 - 22
[48] Cervical Cancer Risk Prediction Model and Analysis of Risk Factors based on Machine Learning
Yang, Wenying
Gou, Xin
Xu, Tongqing
Yi, Xiping
Jiang, Maohong
ICBBT 2019: 2019 11TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL TECHNOLOGY, 2019, : 50 - 54
[49] Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine
Krishna, B. V. Santhosh
Gnanasekaran, T.
CMC-COMPUTERS MATERIALS & CONTINUA, 2019, 60 (03): : 855 - 869
[50] Retinal vessel segmentation under pathological conditions using supervised machine learning
Rani, Priya
Priyadarshini, N.
Rajkumar, E. R.
Rajamani, Kumar
2016 INTERNATIONAL CONFERENCE ON SYSTEMS IN MEDICINE AND BIOLOGY (ICSMB), 2016, : 62 - 66

← 1 2 3 4 5 →