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BioMed Research International
Volume 2014, Article ID 376378, 9 pages
Research Article

Function Formula Oriented Construction of Bayesian Inference Nets for Diagnosis of Cardiovascular Disease

Department of ECE, Faculty of Science & Technology, University of Macau, Avenue Padre Tomas Pereira S.J.S, Macau

Received 6 February 2014; Revised 15 July 2014; Accepted 31 July 2014; Published 27 August 2014

Academic Editor: Aparup Das

Copyright © 2014 Booma Devi Sekar and Mingchui Dong. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An intelligent cardiovascular disease (CVD) diagnosis system using hemodynamic parameters (HDPs) derived from sphygmogram (SPG) signal is presented to support the emerging patient-centric healthcare models. To replicate clinical approach of diagnosis through a staged decision process, the Bayesian inference nets (BIN) are adapted. New approaches to construct a hierarchical multistage BIN using defined function formulas and a method employing fuzzy logic (FL) technology to quantify inference nodes with dynamic values of statistical parameters are proposed. The suggested methodology is validated by constructing hierarchical Bayesian fuzzy inference nets (HBFIN) to diagnose various heart pathologies from the deduced HDPs. The preliminary diagnostic results show that the proposed methodology has salient validity and effectiveness in the diagnosis of cardiovascular disease.