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Development of Health Parameter Model for Risk Prediction of CVD Using SVM
Joint Authors
Arjunan, Sridhar P.
Unnikrishnan, Premith
Kawasaki, Ryo
Kumar, H.
Kumar, Dinesh K.
Mitchell, Paul
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-09
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study.
However, these methods have significant limitations due to their poor sensitivity and specificity.
We have compared the parameters from the Framingham equation with linear regression analysis to establish the effect of training of the model for the local database.
Support vector machine was used to determine the effectiveness of machine learning approach with the Framingham health parameters for risk assessment of cardiovascular disease (CVD).
The result shows that while linear model trained using local database was an improvement on Framingham model, SVM based risk assessment model had high sensitivity and specificity of prediction of CVD.
This indicates that using the health parameters identified using Framingham study, machine learning approach overcomes the low sensitivity and specificity of Framingham model.
American Psychological Association (APA)
Unnikrishnan, Premith& Kumar, Dinesh K.& Arjunan, Sridhar P.& Kumar, H.& Mitchell, Paul& Kawasaki, Ryo. 2016. Development of Health Parameter Model for Risk Prediction of CVD Using SVM. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1100097
Modern Language Association (MLA)
Unnikrishnan, Premith…[et al.]. Development of Health Parameter Model for Risk Prediction of CVD Using SVM. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1100097
American Medical Association (AMA)
Unnikrishnan, Premith& Kumar, Dinesh K.& Arjunan, Sridhar P.& Kumar, H.& Mitchell, Paul& Kawasaki, Ryo. Development of Health Parameter Model for Risk Prediction of CVD Using SVM. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1100097
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100097