ISSN2456-3315
Impact Factor10.57
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CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Breast Cancer Detection Using Machine Learning Techniques
Authors
Anju Kumari , Mohana Vani S , Namitha V Pawar , Vijay Kumar S
Keywords
System Design and Development, Machine Learning, Feature Extraction.
Abstract
Breast cancer is the second leading cause of death for women, so accurate early detection can help decrease
breast cancer mortality rates. This paper aims at giving an overview of breast cancer detection using Machine learning
Technique. The Methodology used here is Convolutional Neural Network with pre-trained model. For the implementation
of the ML algorithms, the dataset was partitioned into the training phase and the testing phase.
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How To Cite
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IJRTI — journal style
"Breast Cancer Detection Using Machine Learning Techniques", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.7, Issue 7, page no.191 - 194, July-2022, Available :https://ijrti.org/papers/IJRTI2207030.pdf
APA — 7th edition
Kumari, A., S, M. V., Pawar, N. V., & S, V. K. (2022). Breast Cancer Detection Using Machine Learning Techniques. International Journal for Research Trends and Innovation, 7(7), 191 - 194. https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030
MLA — 9th edition
Kumari, Anju, et al. "Breast Cancer Detection Using Machine Learning Techniques." International Journal for Research Trends and Innovation, vol. 7, no. 7, 2022, pp. 191 - 194, https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030.
Chicago — 17th, bibliography
Kumari, Anju, et al. "Breast Cancer Detection Using Machine Learning Techniques." International Journal for Research Trends and Innovation 7, no. 7 (2022): 191 - 194. https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030.
Harvard — author–date
Kumari, A. et al. (2022) 'Breast Cancer Detection Using Machine Learning Techniques', International Journal for Research Trends and Innovation, 7(7), pp. 191 - 194. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030
IEEE — numbered reference
A. Kumari, M. V. S, N. V. Pawar and V. K. S, "Breast Cancer Detection Using Machine Learning Techniques," IJRTI, vol. 7, no. 7, pp. 191 - 194, Jul. 2022.
Vancouver — biomedical
Kumari A, S MV, Pawar NV, S VK. Breast Cancer Detection Using Machine Learning Techniques. IJRTI. 2022 Jul;7(7):191 - 194.
AMA — 11th edition
Kumari A, S MV, Pawar NV, S VK. Breast Cancer Detection Using Machine Learning Techniques. IJRTI. 2022;7(7):191 - 194. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2207030,
author = {Anju Kumari and Mohana Vani S and Namitha V Pawar and Vijay Kumar S},
title = {Breast Cancer Detection Using Machine Learning Techniques},
journal = {International Journal for Research Trends and Innovation},
volume = {7},
number = {7},
pages = {191 - 194},
year = {2022},
month = {July},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Kumari, Anju
AU - S, Mohana Vani
AU - Pawar, Namitha V
AU - S, Vijay Kumar
TI - Breast Cancer Detection Using Machine Learning Techniques
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 7
IS - 7
PY - 2022
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030
SP - 191
EP - 194
ER -
Issue
Volume 7 Issue 7,
July-2022
Pages : 191 - 194
Other Publication Details
Paper Reg. ID
IJRTI_182900
Published Paper ID
IJRTI2207030
Downloads
205,618
Research Area
Engineering
Country
Bengaluru, Karnataka, India
Published
July 2022
Published Paper PDF
https://ijrti.org/papers/IJRTI2207030.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2207030
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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Licence
© 2022 — Authors hold the copyright of this article.
This work is licensed under a
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which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Disclaimer:
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.
