UGC Approved Journal no 63975(19)

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Published in:

Volume 9 Issue 12
December-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2212454


Registration ID:
506294

Page Number

e390-e396

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Title

Coronary Heart disease prediction using machine learning

Abstract

The field of medical analysis is often referred to be a valuable source of rich information. Coronary Heart Disease (CHD) is one of the major causes of death all around the world. Therefore, early detection of CHD can help reduce these rates. The challenge lies in the complexity of the data and correlations when it comes to prediction using conventional techniques. The aim of this research is to use the historical medical data to predict CHD using Machine Learning (ML) technology. The scope of this research is limited to using three supervised learning techniques namely Naive Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT), to discover correlations in CHD data that might help improving the prediction rate. Using the South African Heart Disease dataset of 462 instances, intelligent models are derived by the considered ML techniques using 10-fold cross validation. Empirical results using different performance evaluation measures report that probabilistic models derived by NB are promising in detecting CHD.

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"Coronary Heart disease prediction using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 12, page no.e390-e396, December-2022, Available :http://www.jetir.org/papers/JETIR2212454.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Coronary Heart disease prediction using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 12, page no. ppe390-e396, December-2022, Available at : http://www.jetir.org/papers/JETIR2212454.pdf

Publication Details

Published Paper ID: JETIR2212454
Registration ID: 506294
Published In: Volume 9 | Issue 12 | Year December-2022
DOI (Digital Object Identifier):
Page No: e390-e396
Country: Bangalore, Karnataka , India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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