ISSN (online) : 2395 - 7549

 
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A Study on Hierarchical Clustering for Identifying Asthma Endotypes


Author(s):

S. Poorani , KONGU ENGINEERING COLLEGE, PERUNDURAI-638060.; Dr. P. Balasubramanie, KONGU ENGINEERING COLLEGE; N. Sasipriyaa, KONGU ENGINEERING COLLEGE

Keywords:

Data Mining, Hierarchical Clustering, Asthma, Health Care

Abstract:

Large multitudes of medical data are attained due to advancement in recent technology. These large volumes comprise valuable information which helps for diagnosing diseases. Data mining techniques can be used to extract useful patterns from these mass data. It provides a user- oriented approach to the novel and hidden patterns in the data. One of the major challenges in medical domain is the extraction of comprehensible knowledge from medical diagnosis data. Healthcare system needs an automated tool that identifies and disseminates relevant healthcare information. Asthma is one of the dominant disease all over the world. Identifying subtypes of the disease will help in the treatment and prevention approaches. In this paper a clustering model is proposed based on observable symptoms of asthma. The hierarchical clustering technique is used to group the samples based on important characteristics of asthma.

Other Details:

Manuscript Id :J4RV3I5004
Published in :Volume : 3, Issue : 5
Publication Date: 01/08/2017
Page(s): 12-14
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2395 - 7549

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