A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques

S. P. Pavan Kumar; C. M. Samiha; K. S. Anusha; H. L. Gururaj; Ramkumar Krishnamoorthy; Nismon Rio Robert

doi:10.1109/ICDABI53623.2021.9655908

A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques

S. P. Pavan Kumar
, C. M. Samiha
, K. S. Anusha
, H. L. Gururaj
, Ramkumar Krishnamoorthy
, Nismon Rio Robert

Manipal Institute of Technology, Bengaluru

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

Abstract

Heart is one of the significant segments in the human body since it powers blood to the all the pieces of the body. Blood courses through the vein. Cardiovascular sickness is corresponded with the blockage of vein. The sign of heart sickness depends whereupon condition is impacting an individual. The term coronary illness is ordinarily utilized instead of cardiovascular infection. Dilated cardiomyopathy, Heart failure, Arrhythmia, Pulmonary stenosis, Mitral regurgitation, Coronary artery disease, Myocardial infraction, Mitral valve prolapse, Hypertrophic cardiomyopathy are the sorts of coronary illness. The several machine learning techniques are analyzed to spot heart disease. This paper gives relative investigation of coronary illness expectation utilizing machine learning.

Original language	English
Title of host publication	2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	214-217
Number of pages	4
ISBN (Electronic)	9781665416566
DOIs	https://doi.org/10.1109/ICDABI53623.2021.9655908
Publication status	Published - 2021
Event	2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021 - Virtual, Online, Bahrain Duration: 25-10-2021 → 26-10-2021

Publication series

Name	2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021

Conference

Conference	2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021
Country/Territory	Bahrain
City	Virtual, Online
Period	25-10-21 → 26-10-21

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

Business, Management and Accounting (miscellaneous)
Artificial Intelligence
Computer Networks and Communications
Information Systems
Information Systems and Management
Safety, Risk, Reliability and Quality
Health Informatics

Access to Document

10.1109/ICDABI53623.2021.9655908

Cite this

Pavan Kumar, S. P., Samiha, C. M., Anusha, K. S., Gururaj, H. L., Krishnamoorthy, R., & Robert, N. R. (2021). A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques. In 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021 (pp. 214-217). (2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDABI53623.2021.9655908

Pavan Kumar, S. P. ; Samiha, C. M. ; Anusha, K. S. et al. / A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques. 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 214-217 (2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021).

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title = "A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques",

abstract = "Heart is one of the significant segments in the human body since it powers blood to the all the pieces of the body. Blood courses through the vein. Cardiovascular sickness is corresponded with the blockage of vein. The sign of heart sickness depends whereupon condition is impacting an individual. The term coronary illness is ordinarily utilized instead of cardiovascular infection. Dilated cardiomyopathy, Heart failure, Arrhythmia, Pulmonary stenosis, Mitral regurgitation, Coronary artery disease, Myocardial infraction, Mitral valve prolapse, Hypertrophic cardiomyopathy are the sorts of coronary illness. The several machine learning techniques are analyzed to spot heart disease. This paper gives relative investigation of coronary illness expectation utilizing machine learning.",

author = "\{Pavan Kumar\}, \{S. P.\} and Samiha, \{C. M.\} and Anusha, \{K. S.\} and Gururaj, \{H. L.\} and Ramkumar Krishnamoorthy and Robert, \{Nismon Rio\}",

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doi = "10.1109/ICDABI53623.2021.9655908",

language = "English",

series = "2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021",

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

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address = "United States",

}

Pavan Kumar, SP, Samiha, CM, Anusha, KS, Gururaj, HL, Krishnamoorthy, R & Robert, NR 2021, A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques. in 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021. 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021, Institute of Electrical and Electronics Engineers Inc., pp. 214-217, 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021, Virtual, Online, Bahrain, 25-10-21. https://doi.org/10.1109/ICDABI53623.2021.9655908

A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques. / Pavan Kumar, S. P.; Samiha, C. M.; Anusha, K. S. et al.
2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 214-217 (2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021).

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

TY - GEN

T1 - A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques

AU - Pavan Kumar, S. P.

AU - Samiha, C. M.

AU - Anusha, K. S.

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AU - Krishnamoorthy, Ramkumar

AU - Robert, Nismon Rio

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N2 - Heart is one of the significant segments in the human body since it powers blood to the all the pieces of the body. Blood courses through the vein. Cardiovascular sickness is corresponded with the blockage of vein. The sign of heart sickness depends whereupon condition is impacting an individual. The term coronary illness is ordinarily utilized instead of cardiovascular infection. Dilated cardiomyopathy, Heart failure, Arrhythmia, Pulmonary stenosis, Mitral regurgitation, Coronary artery disease, Myocardial infraction, Mitral valve prolapse, Hypertrophic cardiomyopathy are the sorts of coronary illness. The several machine learning techniques are analyzed to spot heart disease. This paper gives relative investigation of coronary illness expectation utilizing machine learning.

AB - Heart is one of the significant segments in the human body since it powers blood to the all the pieces of the body. Blood courses through the vein. Cardiovascular sickness is corresponded with the blockage of vein. The sign of heart sickness depends whereupon condition is impacting an individual. The term coronary illness is ordinarily utilized instead of cardiovascular infection. Dilated cardiomyopathy, Heart failure, Arrhythmia, Pulmonary stenosis, Mitral regurgitation, Coronary artery disease, Myocardial infraction, Mitral valve prolapse, Hypertrophic cardiomyopathy are the sorts of coronary illness. The several machine learning techniques are analyzed to spot heart disease. This paper gives relative investigation of coronary illness expectation utilizing machine learning.

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Pavan Kumar SP, Samiha CM, Anusha KS, Gururaj HL, Krishnamoorthy R, Robert NR. A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques. In 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 214-217. (2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021). doi: 10.1109/ICDABI53623.2021.9655908

A Relative Analysis on the Spotting of Cardiovascular Disease Employing Machine Learning Techniques

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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