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Hybrid Approach for Heart Disease Prediction Using Data Mining Techniques

  • Monther TarawnehEmail author
  • Ossama EmbarakEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 29)

Abstract

Heart disease is one of the significant reason of death and disability. The shortage of Doctors, experts and ignoring patient symptoms lead to big challenge that may cause death, disability to the patient. Therefore, we need expert system that serve as an analysis tool to discover hidden information and patterns in hear disease medical data. Data mining is a cognitive procedure of discovering the hidden approach patterns from large data set. The available massive data can used to extract useful information and relate all attributes to make a decision. Various techniques listed and tested here to understand the accuracy level of each. In previous studies, researchers expressed their effort on finding best prediction model. This paper proposes new heart disease prediction system that combine all techniques into one single algorithm, it called hybridization. The result confirm that accurate diagnose can be taken by using a combined model from all techniques.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.HCTALfujairahUAE

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