Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms

D. Cenitta; R. Vijaya Arjunan; K. V. Prema; G. Vidya Bai

doi:10.1109/ICECCT52121.2021.9616913

Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, according to the World Health Organization: more people die each year from CVDs than from any other cause. CVDs claimed the lives of 17.9 million people worldwide in 2016, accounting for 31% of all deaths. Heart attacks and strokes account for 85 percent of these deaths. The proposed work is about the application of ML (Machine Learning) techniques for the classification and prediction of heart diseases (HD). The scope of the present study includes investigations of main determinants to remove irrelevant and redundant features using the feature selection technique, compare different Machine Learning classification algorithms on the heart disease data set and to identify better performance-based classification technique for heart disease classification.

Original language	English
Title of host publication	2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665414807
DOIs	https://doi.org/10.1109/ICECCT52121.2021.9616913
Publication status	Published - 2021
Event	4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021 - Erode, India Duration: 15-09-2021 → 17-09-2021

Publication series

Name	2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021

Conference

Conference	4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021
Country/Territory	India
City	Erode
Period	15-09-21 → 17-09-21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Hardware and Architecture
Software
Information Systems and Management
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality

Access to Document

10.1109/ICECCT52121.2021.9616913

Cite this

Cenitta, D., Vijaya Arjunan, R., Prema, K. V., & Vidya Bai, G. (2021). Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms. In 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021 (2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECCT52121.2021.9616913

Cenitta, D. ; Vijaya Arjunan, R. ; Prema, K. V. et al. / Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms. 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021).

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title = "Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms",

abstract = "Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, according to the World Health Organization: more people die each year from CVDs than from any other cause. CVDs claimed the lives of 17.9 million people worldwide in 2016, accounting for 31\% of all deaths. Heart attacks and strokes account for 85 percent of these deaths. The proposed work is about the application of ML (Machine Learning) techniques for the classification and prediction of heart diseases (HD). The scope of the present study includes investigations of main determinants to remove irrelevant and redundant features using the feature selection technique, compare different Machine Learning classification algorithms on the heart disease data set and to identify better performance-based classification technique for heart disease classification. ",

author = "D. Cenitta and \{Vijaya Arjunan\}, R. and Prema, \{K. V.\} and \{Vidya Bai\}, G.",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021 ; Conference date: 15-09-2021 Through 17-09-2021",

year = "2021",

doi = "10.1109/ICECCT52121.2021.9616913",

language = "English",

series = "2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021",

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Cenitta, D , Vijaya Arjunan, R , Prema, KV & Vidya Bai, G 2021, Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms. in 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021. 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021, Institute of Electrical and Electronics Engineers Inc., 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021, Erode, India, 15-09-21. https://doi.org/10.1109/ICECCT52121.2021.9616913

Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms. / Cenitta, D.; Vijaya Arjunan, R.; Prema, K. V. et al.
2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms

AU - Cenitta, D.

AU - Vijaya Arjunan, R.

AU - Prema, K. V.

AU - Vidya Bai, G.

PY - 2021

Y1 - 2021

N2 - Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, according to the World Health Organization: more people die each year from CVDs than from any other cause. CVDs claimed the lives of 17.9 million people worldwide in 2016, accounting for 31% of all deaths. Heart attacks and strokes account for 85 percent of these deaths. The proposed work is about the application of ML (Machine Learning) techniques for the classification and prediction of heart diseases (HD). The scope of the present study includes investigations of main determinants to remove irrelevant and redundant features using the feature selection technique, compare different Machine Learning classification algorithms on the heart disease data set and to identify better performance-based classification technique for heart disease classification.

AB - Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, according to the World Health Organization: more people die each year from CVDs than from any other cause. CVDs claimed the lives of 17.9 million people worldwide in 2016, accounting for 31% of all deaths. Heart attacks and strokes account for 85 percent of these deaths. The proposed work is about the application of ML (Machine Learning) techniques for the classification and prediction of heart diseases (HD). The scope of the present study includes investigations of main determinants to remove irrelevant and redundant features using the feature selection technique, compare different Machine Learning classification algorithms on the heart disease data set and to identify better performance-based classification technique for heart disease classification.

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DO - 10.1109/ICECCT52121.2021.9616913

M3 - Conference contribution

AN - SCOPUS:85123405929

T3 - 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021

BT - 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 15 September 2021 through 17 September 2021

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Cenitta D , Vijaya Arjunan R , Prema KV , Vidya Bai G. Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms. In 2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021. Institute of Electrical and Electronics Engineers Inc. 2021. (2021 4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021). doi: 10.1109/ICECCT52121.2021.9616913

Cataloguing of Coronary Heart Malady Using Machine Learning Algorithms

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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