 An e-health decision support framework to predict the heart disordersSruthi Sivakumar and S. Padmavathi International Journal of Business Information Systems, 2020, vol. 34, issue 4, 594-614 Abstract: The current evolutionary usage of data mining techniques can be imparted for the development of medical applications to analyse the health metric. The web-based decision support framework proposed in this work would provide the pre-guidance report based on the decision generated by Bayesian network analysis over the disease dataset. The report is generated in adherence to the mined disease patterns over the patient's non-medical and medical factors which are obtained from the past medical records and predict the possibility of getting the disease for the given similar health metrics. The Bayesian model builds a decision model by analysing the casual intervention effects of the non-medical and medical factors of each individual. The decision model would generate a pre-guidance health report based on the analysed probabilistic chances of getting the heart disorder. The predicted report is a prognostic analysis of the health metric of the individual and suspects their possibility of getting affected by heart disease. Keywords: Bayesian networks; disease pattern analysis; past-clinician heart disease data; e-healthcare; electronic healthcare. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:34:y:2020:i:4:p:594-614 Access Statistics for this article More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd |
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