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An Approach to Data Mining in Healthcare: Improved K-means Algorithm

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dc.contributor.author Nguyen, Dinh Thuan
dc.contributor.author Lam, Vu Tuan Nguyen
dc.contributor.author Nguyen, Gia Toan
dc.contributor.author Hoang, Tung
dc.date.accessioned 2019-07-04T03:40:40Z
dc.date.available 2019-07-04T03:40:40Z
dc.date.issued 2012-02-28
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/397
dc.description.abstract Nowadays, the application of data mining in the healthcare industry is necessary. Data mining brings a set of tools and techniques that can be applied to discover hidden patterns that provide healthcare professionals an additional source of knowledge for making decisions. In more detail, clustering the patients that have the same status helps discovering new disease, but the suitable number of clusters is not often obvious. In this paper, we choose k-means, one of the most popularly used clustering algorithms in the research community, to improve, base on the previous research of the others. en_US
dc.language.iso en en_US
dc.publisher Tenth International Conference On Computer Applications (ICCA 2012) en_US
dc.title An Approach to Data Mining in Healthcare: Improved K-means Algorithm en_US
dc.type Article en_US


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