JOURNAL ARTICLE

Heart Disease Prediction Using Naive Bayes And K-Means Techniques

MS.MEHDI KHUNDMIR ILIYASPROF. VIKAS MARAL

Year: 2017 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Data mining techniques are started gaining its popularity nearly three decades ago. Till last few years data mining approach was not in been used in health care organization. Researchers have started paying attention towards this field, it’s been found by the researcher health care sector is possessing very large volume of data but all this are highly unorganized. If this organized in a proper way using data mining technique it can be easily use for the prediction of various diseases. In this paper author has restricted to heart diseases only. In this paper author has developed a hybrid approach by using two technique Naïve Bayes and K – means algorithm and Hadoop technology. Different 14 parameters are considered by the author for prediction of the heart disease. https://journalnx.com/journal-article/20150364

Keywords:
Naive Bayes classifier Heart disease Popularity Bayes' theorem Health care Volume (thermodynamics)

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Topics

Oral Health Pathology and Treatment
Health Sciences →  Dentistry →  Periodontics
Oral microbiology and periodontitis research
Health Sciences →  Dentistry →  Periodontics
Dental Health and Care Utilization
Health Sciences →  Dentistry →  Periodontics

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