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Leveraging Applications of Data Mining in Healthcare Using Big Data Analytics: An Overview

Leveraging Applications of Data Mining in Healthcare Using Big Data Analytics: An Overview
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Author(s): Mohammad Hossein Tekieh (University of Ottawa, Canada), Bijan Raahemi (University of Ottawa, Canada) and Eric I. Benchimol (University of Ottawa, Canada)
Copyright: 2019
Pages: 15
Source title: Healthcare Policy and Reform: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-6915-2.ch032

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Abstract

Big data analytics has been introduced as a set of scalable, distributed algorithms optimized for analysis of massive data in parallel. There are many prospective applications of data mining in healthcare. In this chapter, the authors investigate whether health data exhibits characteristics of big data, and accordingly, whether big data analytics can leverage the data mining applications in healthcare. To answer this interesting question, potential applications are divided into four categories, and each category into sub-categories in a tree structure. The available types of health data are specified, with a discussion of the applicable dimensions of big data for each sub-category. The authors conclude that big data analytics can provide more advantages for the quality of analysis in particular categories of applications of data mining in healthcare, while having less efficacy for other categories.

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