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

Medicine

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