Paper Title

Prediction of Heart Disease using Soft Computing and Data Mining

Authors

  • K.Sudhakar
  • Dr. M. Manimekalai

Keywords

Cardiovascular Disease, Data Mining, Genetic Algorithm, Neural Networks

Abstract

Cardiovascular disease (CVD) has become the primary killer worldwide and is expected to cause more deaths in the future. Prediction and prevention of CVD have therefore become important social problems. Many groups have developed prediction models for asymptomatic CVD by classifying its risk based on established risk factors (e.g., age, sex, etc.). The growth of medical databases is very high. This rapid growth is the main motivation for researchers to mine useful information from these medical databases. As the volume of stored data increases, data mining techniques play an important role in finding patterns and extracting knowledge to provide better patient care and effective diagnostic capabilities. In the proposed system, the genetic algorithm was first used to reduce the number of attributes that are needed for predicting the cardiovascular disease and then the neural network was employed for prediction of disease from the reduced set of attributes.

Article Type

Published

How To Cite

K.Sudhakar, Dr. M. Manimekalai. "Prediction of Heart Disease using Soft Computing and Data Mining".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 4, pp.3985-3989, URL :https://rjwave.org/ijedr/papers/IJEDR1404097.pdf

Issue

Volume 2 Issue 4 

Pages. 3985-3989

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