Paper Info
Title
A speedy cardiovascular diseases classifier using multiple criteria decision analysis.
Abstract
Each year, some 30 percent of global deaths are caused by cardiovascular diseases. This figure is worsening due to both the increasing elderly population and severe shortages of medical personnel. The development of a cardiovascular diseases classifier (CDC) for auto-diagnosis will help address solve the problem. Former CDCs did not achieve quick evaluation of cardiovascular diseases. In this letter, a new CDC to achieve speedy detection is investigated. This investigation incorporates the analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) to develop feature vectors using a Support Vector Machine. The MCDA facilitates the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. Since the new CDC will only adopt the most meaningful features for discrimination between healthy persons versus cardiovascular disease patients, a speedy detection of cardiovascular diseases has been successfully implemented.
Year
DOI
Venue
2015
10.3390/s150101312
SENSORS
Keywords
Field
DocType
cardiovascular diseases classifier,electrocardiogram,multiple criteria decision analysis,analytic hierarchy process,support vector machine
Population,Data mining,Disease,Feature vector,Multiple-criteria decision analysis,Support vector machine,Electronic engineering,Risk analysis (engineering),Engineering,Classifier (linguistics),Economic shortage,Analytic hierarchy process
Journal
Volume
Issue
ISSN
15
1.0
1424-8220
Citations 
PageRank 
References 
1
0.36
10
Authors
7
Name
Order
Citations
PageRank
Wah Ching Lee132.80
Faan Hei Hung275.99
Kim Fung Tsang352.19
Hoi Ching Tung410.36
Wing-Hong Lau5988.15
Veselin Rakocevic640.76
Loi Lei Lai710.36