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INTERNATIONAL JOURNAL OF PHARMACEUTICAL RESEARCH

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IJPR included in UGC-Approved List of Journals - Ref. No. is SL. No. 4812 & J. No. 63703

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0975-2366
5 - Years Impact Factor

Year 2012 - 2016

Impact Factor: 1.55

Total Publications: 317

Total Citation: 491

Year 2011 - 2015

Impact Factor: 1.46

Total Publications: 326

Total Citation: 477

Year 2010 - 2014

Impact Factor: 1.3

Total Publications: 313

Total Citation: 407

Year 2009 - 2013

Impact Factor: 0.973

Total Publications: 293

Total Citation: 285

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Intelligent Cardiovascular disease prediction using Data mining Techniques

Author: NITHYA S,, RAJASEKHARA BABU M
Abstract: Data mining is a technique which is helpful in identify the pattern in the large dataset. There are many techniques available to work on a huge dataset. But Data mining having much higher advantages comparatively to solve the real world problem. Healthcare mining is an important broad area of data mining and it is considered as one of the important research areas. The classification and Prediction model gives real challenges. To solve this challenges the classification techniques Logistic Regression and Neural network is commonly used.LR conveys that there are one or many independent variables that will determine the problem output. Neural network looks like the human being brain. NN has a collection of neurons. This neurons process the information and transmitting to other neurons. This Paper focus on the feature selection methods similar to forwarding selection and backward elimination using mean evaluation. ANN and LR applied on feature selection methods using Cross-validation sample (CVS) and Percentage Split (PS) as a test option. From the experimental result, it is identified that heart disease dataset using percentage split prediction accuracy of 89.99% is achieved by using 13 attributes with 303 instances for Neural Network as a highest.
Keyword: Cardiovascular disease, Feature selection, Health mining, Logistic regression, Neural Network.
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Impact Factor for five years is 1.55 (2012 - 2016)

Year 2011 - 2015 Impact Factor - 1.46 Total Publications - 326 Total Citations - 477