A Study on the accessible techniques to classify and predict the risk of Cardio Vascular Disease

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-32 Number-1
Year of Publication : 2016
Authors : S. Sivagowry, M. Durairaj
  10.14445/22312803/IJCTT-V32P105

MLA

S. Sivagowry, M. Durairaj "A Study on the accessible techniques to classify and predict the risk of Cardio Vascular Disease". International Journal of Computer Trends and Technology (IJCTT) V32(1):20-27, February 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The health care environment is found to be loaded with information, but deprived in extracting knowledge from the information. This is because of the short of effectual Data Mining tool to determine concealed associations and trends in them. By applying the data mining techniques, important knowledge can be extracted from the health care system. Heart disease is a assemblage of circumstance affecting the arrangement and purpose of heart and has many root causes. Heart disease is the most important cause of fatality in the humankind over past ten years. Research has been made with many hybrid techniques for diagnosing heart disease. This paper deals with an overall appraisal of application of data mining in heart disease prediction.

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Keywords
Data Mining, Heart Disease, Classification, Prediction, Neural Network, Decision Tree, Naïve Bayes.