DocumentCode :
2050633
Title :
An empirical study on applying data mining techniques for the analysis and prediction of heart disease
Author :
Sivagowry, S. ; Durairaj, M. ; Persia, A.
Author_Institution :
Sch. of Comput. Sci. & Eng., Bharathidasan Univ., Trichy, India
fYear :
2013
fDate :
21-22 Feb. 2013
Firstpage :
265
Lastpage :
270
Abstract :
The health care environment is found to be rich in information, but poor in extracting knowledge from the information. This is because of the lack of effective analysis tool to discover hidden relationships and trends in them. By applying the data mining techniques, valuable knowledge can be extracted from the health care system. Heart disease is a group of condition affecting the structure and functions of heart and has many root causes. Heart disease is the leading cause of death in the world over past ten years. Researches have been made with many hybrid techniques for diagnosing heart disease. This paper deals with an overall review of application of data mining in heart disease prediction.
Keywords :
data mining; diseases; health care; medical diagnostic computing; data mining techniques; health care environment; health care system; heart disease diagnosis; knowledge extraction; Accuracy; Association rules; Classification algorithms; Decision trees; Diseases; Heart; Classification; Clustering; Data Mining; Decision Tree; Naïve Bayes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2013 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4673-5786-9
Type :
conf
DOI :
10.1109/ICICES.2013.6508204
Filename :
6508204
Link To Document :
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