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An Evolutionary Algorithm for Heart Disease Prediction

  • M. A. Jabbar
  • B. L. Deekshatulu
  • Priti Chandra
Part of the Communications in Computer and Information Science book series (CCIS, volume 292)

Abstract

This Paper focuses a new approach for applying association rules in the Medical Domain to discover Heart Disease Prediction. The health care industry collects huge amount of health care data which,unfortunately are not mined to discover hidden information for effective decision making.Discovery of hidden patterns and relationships often goes unexploited. Data mining techniques can help remedy this situation.Data mining have found numerous applications in Business and Scientific domains.Association rules,classification,clustering are major areas of interest in data mining. Among these,association rules have been a very active research area.In our work Genetic algorithm is used to predict more accurately the presence of Heart Disease for Andhra Pradesh Population.The main motivation for using Genetic algorithm in the discovery of high level Prediction rules is that they perform a global search and cope better with attribute interaction than the greedy rule induction algorithms often used in Data Mining.

Keywords

Andhra Pradesh Association Rules Evolutionary Computation Heart Disease 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • M. A. Jabbar
    • 1
  • B. L. Deekshatulu
    • 2
  • Priti Chandra
    • 3
  1. 1.JNTUHyderabadIndia
  2. 2.IDRBT, RBI Government of IndiaIndia
  3. 3.Advanced System LaboratoryHyderabadIndia

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