ISSN2456-3315
Impact Factor10.57
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Paper Title
A Review on Human Heart Prediction System Using Machine Learning
Authors
Sangya Ware , Mrs. Shanu .K. Rakesh
Keywords
SVM, Heart Diseases Prediction System, Datamining
Abstract
Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart disease provides more accurate diagnosis than traditional way. In this, a heart disease prediction system which uses SVM algorithm is proposed. 13 clinical features were used as input for the SVM and then the SVM was trained to predict absence or presence of heart disease with accuracy of 95%.
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IJRTI — journal style
"A Review on Human Heart Prediction System Using Machine Learning", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.4, Issue 3, page no.88 - 92, March-2019, Available :https://ijrti.org/papers/IJRTI1903021.pdf
APA — 7th edition
Ware, S., & Rakesh, S. K. (2019). A Review on Human Heart Prediction System Using Machine Learning. International Journal for Research Trends and Innovation, 4(3), 88 - 92. https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021
MLA — 9th edition
Ware, Sangya, and Shanu .K. Rakesh. "A Review on Human Heart Prediction System Using Machine Learning." International Journal for Research Trends and Innovation, vol. 4, no. 3, 2019, pp. 88 - 92, https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021.
Chicago — 17th, bibliography
Ware, Sangya, and Shanu .K. Rakesh. "A Review on Human Heart Prediction System Using Machine Learning." International Journal for Research Trends and Innovation 4, no. 3 (2019): 88 - 92. https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021.
Harvard — author–date
Ware, S. and Rakesh, S.K. (2019) 'A Review on Human Heart Prediction System Using Machine Learning', International Journal for Research Trends and Innovation, 4(3), pp. 88 - 92. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021
IEEE — numbered reference
S. Ware and S. K. Rakesh, "A Review on Human Heart Prediction System Using Machine Learning," IJRTI, vol. 4, no. 3, pp. 88 - 92, Mar. 2019.
Vancouver — biomedical
Ware S, Rakesh SK. A Review on Human Heart Prediction System Using Machine Learning. IJRTI. 2019 Mar;4(3):88 - 92.
AMA — 11th edition
Ware S, Rakesh SK. A Review on Human Heart Prediction System Using Machine Learning. IJRTI. 2019;4(3):88 - 92. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI1903021,
author = {Sangya Ware and Shanu .K. Rakesh},
title = {A Review on Human Heart Prediction System Using Machine Learning},
journal = {International Journal for Research Trends and Innovation},
volume = {4},
number = {3},
pages = {88 - 92},
year = {2019},
month = {March},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Ware, Sangya
AU - Rakesh, Shanu .K.
TI - A Review on Human Heart Prediction System Using Machine Learning
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 4
IS - 3
PY - 2019
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021
SP - 88
EP - 92
ER -
Issue
Volume 4 Issue 3,
March-2019
Pages : 88 - 92
Other Publication Details
Paper Reg. ID
IJRTI_180771
Published Paper ID
IJRTI1903021
Downloads
205,618
Research Area
Engineering
Country
-, -, -
Published
March 2019
Published Paper PDF
https://ijrti.org/papers/IJRTI1903021.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI1903021
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
