ISSN2456-3315
Impact Factor10.57
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CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Heart Disease Prediction Using Machine Learning
Authors
Shreya Pattankude , Aakanksha Vetekar , Sirasappa Y Pattar
Keywords
Heart diseases, Machine learning, Accuracy, Logistic Regression, Prediction
Abstract
Day by day the cases of heart diseases are increasing at a rapid rate and it’s very Important and concerning to predict any such diseases beforehand. This diagnosis is a difficult task i.e. it should be performed precisely and efficiently. The research paper mainly focuses on which patients is more likely to have a heart disease based on various medical attributes. We used machine learning algorithm such as logistic regression and to predict and classify the patient with heart disease. A quite Helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of Heart Attack in any individual.
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IJRTI — journal style
"Heart Disease Prediction Using Machine Learning", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.8, Issue 2, page no.409 - 412, February-2023, Available :https://ijrti.org/papers/IJRTI2302067.pdf
APA — 7th edition
Pattankude, S., Vetekar, A., & Pattar, S. Y. (2023). Heart Disease Prediction Using Machine Learning. International Journal for Research Trends and Innovation, 8(2), 409 - 412. https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067
MLA — 9th edition
Pattankude, Shreya, et al. "Heart Disease Prediction Using Machine Learning." International Journal for Research Trends and Innovation, vol. 8, no. 2, 2023, pp. 409 - 412, https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067.
Chicago — 17th, bibliography
Pattankude, Shreya, Aakanksha Vetekar, and Sirasappa Y Pattar. "Heart Disease Prediction Using Machine Learning." International Journal for Research Trends and Innovation 8, no. 2 (2023): 409 - 412. https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067.
Harvard — author–date
Pattankude, S., Vetekar, A. and Pattar, S.Y. (2023) 'Heart Disease Prediction Using Machine Learning', International Journal for Research Trends and Innovation, 8(2), pp. 409 - 412. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067
IEEE — numbered reference
S. Pattankude, A. Vetekar and S. Y. Pattar, "Heart Disease Prediction Using Machine Learning," IJRTI, vol. 8, no. 2, pp. 409 - 412, Feb. 2023.
Vancouver — biomedical
Pattankude S, Vetekar A, Pattar SY. Heart Disease Prediction Using Machine Learning. IJRTI. 2023 Feb;8(2):409 - 412.
AMA — 11th edition
Pattankude S, Vetekar A, Pattar SY. Heart Disease Prediction Using Machine Learning. IJRTI. 2023;8(2):409 - 412. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2302067,
author = {Shreya Pattankude and Aakanksha Vetekar and Sirasappa Y Pattar},
title = {Heart Disease Prediction Using Machine Learning},
journal = {International Journal for Research Trends and Innovation},
volume = {8},
number = {2},
pages = {409 - 412},
year = {2023},
month = {February},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Pattankude, Shreya
AU - Vetekar, Aakanksha
AU - Pattar, Sirasappa Y
TI - Heart Disease Prediction Using Machine Learning
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 8
IS - 2
PY - 2023
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067
SP - 409
EP - 412
ER -
Issue
Volume 8 Issue 2,
February-2023
Pages : 409 - 412
Other Publication Details
Paper Reg. ID
IJRTI_185307
Published Paper ID
IJRTI2302067
Downloads
205,671
Research Area
Bio Medical EngineeringÂ
Country
Bangalore, Karnataka, India
Published
February 2023
Published Paper PDF
https://ijrti.org/papers/IJRTI2302067.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2302067
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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© 2023 — Authors hold the copyright of this article.
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The content, data and findings in this article are based on the authors’ research and have been
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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.
