Clustering as a Data Mining Technique in Health Hazards of High levels of Fluoride in Potable Water
R. T Balasubramanian. International Journal of Advanced Computer Science and Applications(IJACSA), (2012)
Zusammenfassung
This article explores data mining techniques in health care. In particular, it discusses data mining and its application in areas where people are affected severely by using the under- ground drinking water which consist of high levels of fluoride in Krishnagiri District, Tamil Nadu State, India. This paper identifies the risk factors associated with the high level of fluoride content in water, using clustering algorithms and finds meaningful hidden patterns which gives meaningful decision making to this socio-economic real world health hazard. 2
%0 Journal Article
%1 IJACSA.2012.030228
%A T Balasubramanian, R.Umarani
%D 2012
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Clustering, Fluoride K-means, Skeletal.,Data affected mining people,
%N 2
%T Clustering as a Data Mining Technique in Health Hazards of High levels of Fluoride in Potable Water
%U http://ijacsa.thesai.org/
%V 3
%X This article explores data mining techniques in health care. In particular, it discusses data mining and its application in areas where people are affected severely by using the under- ground drinking water which consist of high levels of fluoride in Krishnagiri District, Tamil Nadu State, India. This paper identifies the risk factors associated with the high level of fluoride content in water, using clustering algorithms and finds meaningful hidden patterns which gives meaningful decision making to this socio-economic real world health hazard. 2
@article{IJACSA.2012.030228,
abstract = {This article explores data mining techniques in health care. In particular, it discusses data mining and its application in areas where people are affected severely by using the under- ground drinking water which consist of high levels of fluoride in Krishnagiri District, Tamil Nadu State, India. This paper identifies the risk factors associated with the high level of fluoride content in water, using clustering algorithms and finds meaningful hidden patterns which gives meaningful decision making to this socio-economic real world health hazard. [2]
},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{T Balasubramanian}, R.Umarani},
biburl = {https://www.bibsonomy.org/bibtex/2f70e50e263b2e50ebf28e4e4fa68d601/thesaiorg},
interhash = {db4372d8d47afc4e642812647b3d3ac5},
intrahash = {f70e50e263b2e50ebf28e4e4fa68d601},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {Clustering, Fluoride K-means, Skeletal.,Data affected mining people,},
number = 2,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{Clustering as a Data Mining Technique in Health Hazards of High levels of Fluoride in Potable Water}},
url = {http://ijacsa.thesai.org/},
volume = 3,
year = 2012
}