INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
DATA MINING CLASSIFIERS IN THE PREDICTION OF HEART DISEASE
Authors Name:
S.THARANI
, P.KARTHIK
Unique Id:
IJSDR2006125
Published In:
Volume 5 Issue 6, June-2020
Abstract:
The Healthcare industry is generally information rich but unluckily not all the data are mined which is required for discover hidden patterns & effective decision making. Data mining techniques are used to notice knowledge in database and for medical research, mainly in Heart disease prediction. Cardiovascular disease connecting high death rates Angiography is, more frequently than not, regarded as the best system for the examination of coronary artery disease; on the other hand, it was connected with significant side effects and high costs. Much investigation has, consequently, be conveyed using data mining and machine learning to attempt alternative modalities cardiovascular disease includes coronary heart disease (CHD), cerebrovascular disease (stroke) , Hypertensive heart disease, congenital heart disease peripheral artey disease , rheumatic heart disease, inflammatory heart disease . The main cause of cardiovascular disease is tobacco use, physical inactivity, an unhealthy diet and harmful use of alcohol. Complex data mining benefits from the past experience and algorithm defined with existing software and packages , with certain tools gaining a greater affinity or reputation with different techniques .In this project, the various supervised machine learning classifiers like K-Nearest neighbor and support vector machine is used to identify the heart disease.
Keywords:
Data Mining, Heart Disease, coronary heart disease (CHD), K-Nearest neighbor, support vector machine
Cite Article:
"DATA MINING CLASSIFIERS IN THE PREDICTION OF HEART DISEASE", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 6, page no.746 - 752, June-2020, Available :http://www.ijsdr.org/papers/IJSDR2006125.pdf
Downloads:
000337211
Publication Details:
Published Paper ID: IJSDR2006125
Registration ID:192077
Published In: Volume 5 Issue 6, June-2020
DOI (Digital Object Identifier):
Page No: 746 - 752
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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