A STUDY ON EFFECTIVE CLASSIFICATION AND PREDICTION OF HEART DISEASE USING DATA MINING TECHNIQUES
Sri Vasavi College, Erode Self-Finance Wing, 3rd February 2017. National Conference on Computer and Communication, NCCC’17. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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The objective of our work is to analyze various data mining tools and techniques in health care domain that can be employed in prediction of heart disease system and their efficient diagnosis. There is a growing need in the health care scenario to store and organize sizeable clinical data, analyze the data, assist the health care professionals in decision making, and develop data mining methodologies to mine hidden patterns and discover new knowledge from clinical data. Healthcare industry today generates large amounts of complex data about patients, hospitals resources, disease diagnosis, electronic patient records, medical devices etc. The large amounts of data are a key resource to be processed and analyzed for knowledge extraction that enables support for cost savings and decision making. Data mining brings a set of tools and techniques that can be applied to this processed data to discover hidden patterns that provide healthcare professionals an additional source of knowledge for making decisions. Classification techniques are greatly deployed in several application domains for the purpose of classification, estimation and prediction. In this paper we survey different papers in which one or more algorithms of data mining used for the prediction of heart disease.
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Data Mining, Heart Disease, Health Care, Classification Techniques