A Bayesian network model for predicting cardiovascular risk

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Apr 2023Embargo end date: 01 Jan 2021 Spain, Spain English Publisher:Elsevier BVJournal:Computer Methods and Programs in Biomedicine, volume 231, page 107,405 (issn: 0169-2607,

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Authors: José M. Ordovás; David Ríos Insua; Alejandro Santos-Lozano; Alejandro Lucia; A. Torres; Alex Kosgodagan; José Manuel Camacho;

doi: 10.1016/j.cmpb.2023.107405 , 10.48550/arxiv.2112.13963

pmid: 36796167

arXiv: 2112.13963

handle: 10261/346387

A Bayesian network model for predicting cardiovascular risk

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Abstract

We propose a Bayesian network model to make inferences and predictions about cardiovascular risk. Both the structure and the probability tables in the underlying model are built using a large dataset collected in Spain from annual work health assessments, with uncertainty characterized through posterior distributions. We illustrate its use for public health practice, policy and research purposes. A freely available version of the software is included in an Appendix.

16 pages, 7 tables, 2 figures, companion software (free for academic use) Update: Format edited

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Spain, Spain

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Keywords

FOS: Computer and information sciences, J.3, Disease treatment, 62C10, Healthcare, I.2.m; J.3, Bayes Theorem, I.2.m, Statistics - Applications, Health policy, Bayesian networks, Cardiovascular diseases, Cardiovascular Diseases, Risk Factors, Heart Disease Risk Factors, Humans, Applications (stat.AP), Software

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