NDLI: Using data mining techniques in heart disease diagnosis and treatment

Content Provider	IEEE Xplore Digital Library
Author	Shouman, M. Turner, T. Stocker, R.
Copyright Year	2012
Description	Author affiliation: School of Engineering and Information Technology, University of New South Wales at the Australian Defence Force Academy, Northcott Drive, Canberra ACT 2600, Australia (Shouman, M.; Turner, T.; Stocker, R.)
Abstract	The availability of huge amounts of medical data leads to the need for powerful data analysis tools to extract useful knowledge. Researchers have long been concerned with applying statistical and data mining tools to improve data analysis on large data sets. Disease diagnosis is one of the applications where data mining tools are proving successful results. Heart disease is the leading cause of death all over the world in the past ten years. Several researchers are using statistical and data mining tools to help health care professionals in the diagnosis of heart disease. Using single data mining technique in the diagnosis of heart disease has been comprehensively investigated showing acceptable levels of accuracy. Recently, researchers have been investigating the effect of hybridizing more than one technique showing enhanced results in the diagnosis of heart disease. However, using data mining techniques to identify a suitable treatment for heart disease patients has received less attention. This paper identifies gaps in the research on heart disease diagnosis and treatment and proposes a model to systematically close those gaps to discover if applying data mining techniques to heart disease treatment data can provide as reliable performance as that achieved in diagnosing heart disease.
Starting Page	173
Ending Page	177
File Size	245361
Page Count	5
File Format	PDF
ISBN	9781467304856
e-ISBN	9781467304849
DOI	10.1109/JEC-ECC.2012.6186978
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-06
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart Accuracy Heart Disease Diagnosis and Treatment Data Mining E-health Data mining Decision trees Medical diagnostic imaging Diseases
Content Type	Text
Resource Type	Article

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