HEART DISEASE PREDICTION SYSTEM USING DATA MINING TECHNIQUES

Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17

Format: Volume 5, Issue 1, No 1, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: C.Sowmiya, Dr.P. Sumitra

Reference:IJCS-157

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Abstract

Data mining is process to analyses number of data sets and then extracts the meaning of data. It helps to predict the patterns and future trends, allowing business in decision making. Data mining applications are able to give the answer of business questions which can take much time to resolve traditionally. High amount of data that can be generated for the prediction of disease is analyzed traditionally and is too complicated along with voluminous to be processed. Data mining provides methods and techniques for transformation of the data into useful information for decision making. These techniques can make process fast and take less time to predict the heart disease with more accuracy. The healthcare sector assembles enormous quantity of healthcare data which cannot be mined to uncover hidden information for effectual decision making. However, there is a plenty of hidden information in this data which is untapped and not being used appropriately for predictions. It becomes more influential in case of heart disease that is considered as the predominant reason behind death all over the world. In medical field, Data Mining provides several methods which are widely used in the medical and clinical decision support systems which should be helpful for diagnosis and predicting of various diseases. These data mining techniques can be used in heart diseases takes less time and make the process much faster for the prediction system to predict diseases with good accuracy to improve their health.

References

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Keywords

Heart disease, Prediction, Classification, Decision Table, Bayesian Classifiers.

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