Continuous Dynamic Bayesian networks for predicting survival of ischaemic heart disease patients

Adele H. Marshall*, Laura A. Hill, Frank Kee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper introduces a Dynamic Bayesian network (DBN) model for representing survival of patients suffering from ischaemic heart disease (IHD). The main purpose of the model is to investigate the potential association between patient variables, the risk of developing cardiovascular disease (IHD) and survival. Of particular interest is whether, a combination of risk factors known as Metabolic syndrome are the key variables of interest in determining IHD risk or whether there are others considered just as significant, such as age, smoking and BMI that are not associated with the syndrome. The resulting Dynamic Bayesian network provides a straightforward illustration of the causal relationships between patient variables, disease occurrence and survival with the aim of understanding patient needs and the possibility of highlighting health interventions. It is hoped that such a model can help inform patient management decisions by illustrating where a change in certain patient characteristics could produce a health improvement and reduced risk. The DBN has the additional capacity to allow the representation of repeated measures data where patient variables may be available at more than one time point.

Original languageEnglish
Title of host publicationProceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
Pages178-183
Number of pages6
DOIs
Publication statusPublished - 01 Dec 2010
Event23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010 - Perth, Australia
Duration: 12 Oct 201015 Oct 2010

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)1063-7125

Conference

Conference23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
CountryAustralia
CityPerth
Period12/10/201015/10/2010

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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