Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk

Highlights • An epidemiologic system analysis of cardiovascular risk is presented through a Bayesian network model. • The Bayesian network model can serve as a generic tool for application oriented activities: explanation, prediction, monitoring and prevention. • Due to cardiovascular disease is mul...

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Bibliographic Details
Published inComputer methods and programs in biomedicine Vol. 126; pp. 128 - 142
Main Authors Fuster-Parra, P, Tauler, P, Bennasar-Veny, M, Ligęza, A, López-González, A.A, Aguiló, A
Format Journal Article
LanguageEnglish
Published Ireland Elsevier Ireland Ltd 01.04.2016
Subjects
Adult
Algorithms
Artificial Intelligence
Bayes Theorem
Bayesian analysis
Bayesian networks
Body Mass Index
Body Weight
Cardiovascular Diseases - epidemiology
Cardiovascular lost years
Cardiovascular risk score
Cardiovascular System
Causal dependency discovery
Epidemiology
Female
Humans
Internal Medicine
Male
Mathematical models
Metabolic syndrome
Middle Aged
Model averaging
Modelling
Models, Cardiovascular
Models, Statistical
Other
Reasoning
Risk
Risk analysis
Risk Factors
Smoking
Cardiovascular lost years
Bayesian networks
Cardiovascular risk score
Metabolic syndrome
Model averaging
Causal dependency discovery
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Summary:Highlights • An epidemiologic system analysis of cardiovascular risk is presented through a Bayesian network model. • The Bayesian network model can serve as a generic tool for application oriented activities: explanation, prediction, monitoring and prevention. • Due to cardiovascular disease is multifactorial, the application of this kind of model is of special interest, both from theoretical and practical point of view. • The induced Bayesian network was used to make inferences taking into account three reasoning patterns: causal reasoning, evidential reasoning, and intercausal reasoning.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0169-2607
1872-7565
DOI:10.1016/j.cmpb.2015.12.010