Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases

Boomadevi Sekar, Ming Chui Dong, Jiayi Dou

Research output: Contribution to journalArticle

Abstract

A generalized Bayesian inference nets model (GBINM) is proposed to aid researchers to construct Bayesian inference nets for various applications. The benefit of such a model is well demonstrated by applying GBINM in constructing a hierarchical Bayesian fuzzy inference nets (HBFIN) to diagnose five important types of cardiovascular diseases (CVD). The patients’ medical records with doctors’ confirmed diagnostic results obtained from two hospitals in China are used to design and verify HBFIN. Bayesian theorem is used to calculate the propagation of probability and address the uncertainties involved in each sequential stage of inference nets to deduce the disease(s). The validity and effectiveness of proposed approach is witnessed clearly from testing results obtained.
LanguageEnglish
Pages209-225
Number of pages17
JournalJournal of Intelligent Systems
Volume20
Issue number3
DOIs
Publication statusPublished - 2011

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Fuzzy inference
Testing
Uncertainty

Cite this

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abstract = "A generalized Bayesian inference nets model (GBINM) is proposed to aid researchers to construct Bayesian inference nets for various applications. The benefit of such a model is well demonstrated by applying GBINM in constructing a hierarchical Bayesian fuzzy inference nets (HBFIN) to diagnose five important types of cardiovascular diseases (CVD). The patients’ medical records with doctors’ confirmed diagnostic results obtained from two hospitals in China are used to design and verify HBFIN. Bayesian theorem is used to calculate the propagation of probability and address the uncertainties involved in each sequential stage of inference nets to deduce the disease(s). The validity and effectiveness of proposed approach is witnessed clearly from testing results obtained.",
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Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases. / Sekar, Boomadevi; Dong, Ming Chui; Dou, Jiayi.

In: Journal of Intelligent Systems, Vol. 20, No. 3, 2011, p. 209-225.

Research output: Contribution to journalArticle

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AU - Dong, Ming Chui

AU - Dou, Jiayi

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AB - A generalized Bayesian inference nets model (GBINM) is proposed to aid researchers to construct Bayesian inference nets for various applications. The benefit of such a model is well demonstrated by applying GBINM in constructing a hierarchical Bayesian fuzzy inference nets (HBFIN) to diagnose five important types of cardiovascular diseases (CVD). The patients’ medical records with doctors’ confirmed diagnostic results obtained from two hospitals in China are used to design and verify HBFIN. Bayesian theorem is used to calculate the propagation of probability and address the uncertainties involved in each sequential stage of inference nets to deduce the disease(s). The validity and effectiveness of proposed approach is witnessed clearly from testing results obtained.

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