Title: An e-health decision support framework to predict the heart disorders

Authors: Sruthi Sivakumar; S. Padmavathi

Addresses: Department of Information Technology, PSG College of Engineering, Coimbatore, Tamil Nadu, India ' Department of Information Technology, Thiagarajar College of Engineering, Madurai, Tamil Nadu, India

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.

DOI: 10.1504/IJBIS.2020.109023

International Journal of Business Information Systems, 2020 Vol.34 No.4, pp.594 - 614

Accepted: 03 Jul 2018
Published online: 17 Aug 2020 *

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