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A Survey on Early Detection and Prediction of Heart Diseases using Machine Learning and Data Mining Techniques

Bhumika J.1 , Rashmi R. Kotiyan2 , Sonal T.H.3 , Lakshmi R.4

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-2 , Page no. 31-34, Feb-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i2.3134

Online published on Feb 28, 2020

Copyright © Bhumika J., Rashmi R. Kotiyan, Sonal T.H., Lakshmi R. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Bhumika J., Rashmi R. Kotiyan, Sonal T.H., Lakshmi R., “A Survey on Early Detection and Prediction of Heart Diseases using Machine Learning and Data Mining Techniques,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.2, pp.31-34, 2020.

MLA Style Citation: Bhumika J., Rashmi R. Kotiyan, Sonal T.H., Lakshmi R. "A Survey on Early Detection and Prediction of Heart Diseases using Machine Learning and Data Mining Techniques." International Journal of Computer Sciences and Engineering 8.2 (2020): 31-34.

APA Style Citation: Bhumika J., Rashmi R. Kotiyan, Sonal T.H., Lakshmi R., (2020). A Survey on Early Detection and Prediction of Heart Diseases using Machine Learning and Data Mining Techniques. International Journal of Computer Sciences and Engineering, 8(2), 31-34.

BibTex Style Citation:
@article{J._2020,
author = {Bhumika J., Rashmi R. Kotiyan, Sonal T.H., Lakshmi R.},
title = {A Survey on Early Detection and Prediction of Heart Diseases using Machine Learning and Data Mining Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2020},
volume = {8},
Issue = {2},
month = {2},
year = {2020},
issn = {2347-2693},
pages = {31-34},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5026},
doi = {https://doi.org/10.26438/ijcse/v8i2.3134}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i2.3134}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5026
TI - A Survey on Early Detection and Prediction of Heart Diseases using Machine Learning and Data Mining Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - Bhumika J., Rashmi R. Kotiyan, Sonal T.H., Lakshmi R.
PY - 2020
DA - 2020/02/28
PB - IJCSE, Indore, INDIA
SP - 31-34
IS - 2
VL - 8
SN - 2347-2693
ER -

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Abstract

Cardio vascular disease is the most prominent cause of death worldwide. Machine Learning Algorithms can be used for predicting chances of heart disease occurrence.  Relating machine learning and data mining methods is a strategic approach to consume large volumes of available Cardio-related data for prediction. The datasets used are classified in terms of medical parameters. In this paper, numerous algorithms and techniques are discussed that are used in prediction of Cardio Vascular Diseases. Fast Correlation-Based Feature Selection (FCBF) method to filter noise data to improve quality of heart disease classification. K-Nearest Neighbour, Support Vector Machine, Naïve Bayes, Random Forest and a Multilayer Perception, Artificial Neural Network optimized by Particle Swarm Optimization (PSO) combined with Ant Colony Optimization (ACO) are the classification algorithms used. By using machine learning algorithms and deep learning it provides numerous ways for the prediction of the heart disease. There are various methods which provide us an information and these are applied to various datasets to get particular results. 

Key-Words / Index Term

Heart Disease, Predictive Analysis, Naïve Bayes, Decision Tree, SVM

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