Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases

Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases

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 i...

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Main Authors: Sekar Booma Devi, Dong Mingchui, Dou Jiayi
Format: Article
Language:English
Published: De Gruyter 2011-11-01
Series:Journal of Intelligent Systems
Subjects:
generalized bayesian inference nets model
statistical parameters
diagnosis of cardiovascular disease
Online Access:https://doi.org/10.1515/jisys.2011.012
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spelling doaj-3fa57827f05d45fdb79f043b08bc803c2021-09-06T19:40:40ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2011-11-0120320922510.1515/jisys.2011.012Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular DiseasesSekar Booma Devi0Dong Mingchui1Dou Jiayi2Faculty of Science and Technology, University of Macau, Avenida Padre Tomas Pereira, Taipa Macau SAR, China.Faculty of Science and Technology, University of Macau, Avenida Padre Tomas Pereira, Taipa Macau SAR, China.Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, USA.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.https://doi.org/10.1515/jisys.2011.012generalized bayesian inference nets modelstatistical parametersdiagnosis of cardiovascular disease
collection DOAJ
language English
format Article
sources DOAJ
author Sekar Booma Devi
Dong Mingchui
Dou Jiayi
spellingShingle Sekar Booma Devi
Dong Mingchui
Dou Jiayi
Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases
Journal of Intelligent Systems
generalized bayesian inference nets model
statistical parameters
diagnosis of cardiovascular disease
author_facet Sekar Booma Devi
Dong Mingchui
Dou Jiayi
author_sort Sekar Booma Devi
title Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases
title_short Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases
title_full Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases
title_fullStr Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases
title_full_unstemmed Generalized Bayesian Inference Nets Model and Diagnosis of Cardiovascular Diseases
title_sort generalized bayesian inference nets model and diagnosis of cardiovascular diseases
publisher De Gruyter
series Journal of Intelligent Systems
issn 0334-1860
2191-026X
publishDate 2011-11-01
description 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.
topic generalized bayesian inference nets model
statistical parameters
diagnosis of cardiovascular disease
url https://doi.org/10.1515/jisys.2011.012
work_keys_str_mv AT sekarboomadevi generalizedbayesianinferencenetsmodelanddiagnosisofcardiovasculardiseases
AT dongmingchui generalizedbayesianinferencenetsmodelanddiagnosisofcardiovasculardiseases
AT doujiayi generalizedbayesianinferencenetsmodelanddiagnosisofcardiovasculardiseases
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