Paper Info
Title
Novel Approaches for Predicting Risk Factors of Atherosclerosis.
Abstract
Coronary heart disease (CHD) caused by hardening of artery walls due to cholesterol known as atherosclerosis is responsible for large number of deaths world-wide. The disease progression is slow, asymptomatic and may lead to sudden cardiac arrest, stroke or myocardial infraction. Presently, imaging techniques are being employed to understand the molecular and metabolic activity of atherosclerotic plaques to estimate the risk. Though imaging methods are able to provide some information on plaque metabolism they lack the required resolution and sensitivity for detection. In this paper we consider the clinical observations and habits of individuals for predicting the risk factors of CHD. The identification of risk factors helps in stratifying patients for further intensive tests such as nuclear imaging or coronary angiography. We present a novel approach for predicting the risk factors of atherosclerosis with an in-built imputation algorithm and particle swarm optimization (PSO). We compare the performance of our methodology with other machine learning techniques on STULONG dataset which is based on longitudinal study of middle aged individuals lasting for twenty years. Our methodology powered by PSO search has identified physical inactivity as one of the risk factor for the onset of atherosclerosis in addition to other already known factors. The decision rules extracted by our methodology are able to predict the risk factors with an accuracy of $99.73%$ which is higher than the accuracies obtained by application of the state-of-the-art machine learning techniques presently being employed in the identification of atherosclerosis risk studies.
Year
DOI
Venue
2013
10.1109/TITB.2012.2227271
Biomedical and Health Informatics, IEEE Journal of
Keywords
DocType
Volume
Atherosclerosis,classification,decision trees,feature selection,imputation,particle swarm optimization (PSO),prediction,risk factors
Journal
abs/1501.07093
Issue
ISSN
Citations 
1
Biomedical and Health Informatics, IEEE Journal of , vol.17, no.1, pp.183,189, Jan. 2013
3
PageRank 
References 
Authors
0.46
10
2
Name
Order
Citations
PageRank
V. Sree Hari Rao19312.87
M. Naresh Kumar271.65