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Hybrid Data Mining for Medical Applications

Hybrid Data Mining for Medical Applications
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Author(s): Syed Zahid Hassan (Central Queensland University, Australia) and Brijesh Verma (Central Queensland University, Australia)
Copyright: 2009
Pages: 21
Source title: Handbook of Research on Modern Systems Analysis and Design Technologies and Applications
Source Author(s)/Editor(s): Mahbubur Rahman Syed (Minnesota State University Mankato, USA) and Sharifun Nessa Syed (Minnesota State University - Mankato, USA)
DOI: 10.4018/978-1-59904-887-1.ch029

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Abstract

This chapter focuses on hybrid data mining algorithms and their use in medical applications. It reviews existing data mining algorithms and presents a novel hybrid data mining approach, which takes advantage of intelligent and statistical modeling of data mining algorithms to extract meaningful patterns from medical data repositories. Various hybrid combinations of data mining algorithms are formulated and tested on a benchmark medical database. The chapter includes the experimental results with existing and new hybrid approaches to demonstrate the superiority of hybrid data mining algorithms over standard algorithms.

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