Review of Heart Disease Prediction Using Data Mining Techniques

Author(s):

M. Revathi , Sri Paramakalyani College, Alwarkurichi, Tirunelveli District

Keywords:

Data Mining, Decision Trees, Ensemble Classifiers, Genetic Algorithm, Heart Disease, Naive Bayes, Neural Networks and SVM

Abstract:

Health care data includes patient centric data, their treatment data and resource management data. It is very massive and information rich. Data mining techniques have been used in healthcare research and known to be effective. The Healthcare industry is generally “information rich”, which is not feasible to handle manually. These large amounts of data are very important in the field of Data Mining to extract useful information and generate relationships amongst the attributes. The doctors and experts available are not in proportion with the population. Also, symptoms often be neglected. Heart disease diagnosis is a complex task which requires much experience and knowledge. Heart disease is a single largest cause of death in developed countries and one of the main contributors to disease burden in developing countries. In the health care industry the data mining is mainly used for predicting the diseases from the datasets. The Data Mining techniques, namely SVM, Ensemble Classifier methods, Decision Trees, Naive Bayes, Neural Networks and Genetic Algorithm are analyzed on Heart disease database.

Other Details:

Manuscript Id	:	IJSTEV2I10299
Published in	:	Volume : 2, Issue : 10
Publication Date	:	01/05/2016
Page(s)	:	1179-1182

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