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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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A state of art heart disease prediction techniques based on evolutionary algorithms

Author: R. SELVI
Abstract: In the past decades, heart disease (HD) is an important reason for the increased mortality rate. It is a demanding problem to build powerful and reliable medical decision support systems (MDSS) to diminish the diagnosing time and enhancing the accuracy of diagnosis. Among the massive data, to explore the hidden patterns, data mining provides various approaches. From the medical data of patient, HD can be diagnosed using the data mining approaches. Various classification algorithms are built to diagnose the HD correctly. Classification rule mining is a significant job in the data mining development which is planned to search a tiny collection of rules out of the training data set. This paper reviews several classification algorithms based on evolutionary algorithms (EA) developed for the prediction of HD in various aspects. A detailed review is made based on the objectives, methodology used, advantages, performance measures used and so on. At the end of the paper, a comparative analysis is made based on different metrics.
Keyword: Heart disease, Classification, Machine learning, Disease prediction.
DOI: https://doi.org/10.31838/ijpr/2019.11.01.091
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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