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A Optimized Binary Approach for Heart Disease Decision Model in Biomedical Data Mining

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 12
Year of Publication: 2016
Authors:
Sonika Rana, Sukhjot Kaur
10.5120/ijca2016912411

Sonika Rana and Sukhjot Kaur. A Optimized Binary Approach for Heart Disease Decision Model in Biomedical Data Mining. International Journal of Computer Applications 156(12):1-5, December 2016. BibTeX

@article{10.5120/ijca2016912411,
	author = {Sonika Rana and Sukhjot Kaur},
	title = {A Optimized Binary Approach for Heart Disease Decision Model in Biomedical Data Mining},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {12},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume156/number12/26758-2016912411},
	doi = {10.5120/ijca2016912411},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Heart diseases are the most common cause of death across worldwide. Due to the huge amount of data obtained from medical sector, hidden patterns remain hidden and knowledge cannot be extract from the database. This will result into loss of required information and treatment cannot be done accordingly. Several techniques have been proposed till now to find the effect of disease at earlier stage but still it is under consideration. Data mining is used to extract useful information from the database. Consequently, data analyses tool can be used to fetch required information from the database and effective decision can be made. Traditionally various heart disease detection techniques have been proposed like decision tree, genetic algorithm and so on.

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Keywords

Data Mining, Heart Disease, BPSO, Neural Network.