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A speedy cardiovascular diseases classifier using multiple criteria decision analysis

Lee, W. C., Hung, F. H., Tsang, K. F., Tung, H. C., Lau, W. H., Rakocevic, V. and Lai, L. (2014). A speedy cardiovascular diseases classifier using multiple criteria decision analysis. Sensors, 15(1), pp. 1312-1320. doi: 10.3390/s150101312

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.

Publication Type: Article
Additional Information: Copyright MDPI 2015
Publisher Keywords: cardiovascular diseases classifier; electrocardiogram; multiple criteria decision analysis; analytic hierarchy process; support vector machine
Subjects: R Medicine > RC Internal medicine
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments: School of Mathematics, Computer Science & Engineering > Engineering
School of Mathematics, Computer Science & Engineering > Engineering > Electrical & Electronic Engineering
URI: http://openaccess.city.ac.uk/id/eprint/5964
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