DATA MINING CLASSIFIERS IN THE PREDICTION OF HEART DISEASE
Data Mining, Heart Disease, coronary heart disease (CHD), K-Nearest neighbor, support vector machine
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.
"DATA MINING CLASSIFIERS IN THE PREDICTION OF HEART DISEASE", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 6, page no.746 - 752, June-2020, Available :https://ijsdr.org/papers/IJSDR2006125.pdf
Volume 5
Issue 6,
June-2020
Pages : 746 - 752
Paper Reg. ID: IJSDR_192077
Published Paper Id: IJSDR2006125
Downloads: 000347207
Research Area: Engineering
Country: THIRUVAUR, TAMIL NADU, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
