Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm

Soumyalatha Naveen; Nachiketh V. Kashyap; Varun P. Kulkarni; A. Sandeep; Meruva Sai Chakradhar

doi:10.1109/ViTECoN58111.2023.10157765

Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm

Soumyalatha Naveen
, Nachiketh V. Kashyap
, Varun P. Kulkarni
, A. Sandeep
, Meruva Sai Chakradhar

School of Computer Engineering

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

1 Citation (Scopus)

Abstract

Breast cancer is a highly deadly and common cancer that is spreading over the world and claiming many lives. Breast cancer develops in the glandular tissue of the breast in the lining of epithelial cells of ducts or (15%) lobules. These tissues heal with time. These in situ tumours may develop over time and infect the breast cells' immediate environs (stage 1), impact the lymph nodes, and finally totally spread throughout the body's organs (stage 3). There were 685,000 deaths worldwide in 2020 and a later rise in the number of malignant women. Cancer was a common disease that affected 7.8 million of the female population. The k-means algorithm is a popular data clustering algorithm. As the main analytical routine in data mining, the techniques of the clustering algorithm will impact the clustering outcome directly. This paper examines the shortcomings of the standard k-means algorithm and discusses them. This paper reviews existing methods for selecting the number of clusters for the algorithm. However, one of its drawbacks is the requirement that the number of clusters, K, be specified before the algorithm is applied. Therefore, we obtained an accuracy of 85% after executing the program, and we were able to depict the difference between a benign and a malignant tumour. And we were able to see the centroid between the two tumours.

Original language	English
Title of host publication	ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings
Editors	Thanikaiselvan V Thanikaiselvan V, Renuga Devi S, Shankar T, Kalaivani S
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350347982
DOIs	https://doi.org/10.1109/ViTECoN58111.2023.10157765
Publication status	Published - 2023
Event	2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023 - Vellore, India Duration: 05-05-2023 → 06-05-2023

Publication series

Name	ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings

Conference

Conference	2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023
Country/Territory	India
City	Vellore
Period	05-05-23 → 06-05-23

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

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Hardware and Architecture
Instrumentation

Access to Document

10.1109/ViTECoN58111.2023.10157765

Cite this

Naveen, S., Kashyap, N. V., Kulkarni, V. P., Sandeep, A., & Chakradhar, M. S. (2023). Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm. In T. V. Thanikaiselvan V, R. D. S, S. T, & K. S (Eds.), ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings (ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ViTECoN58111.2023.10157765

Naveen, Soumyalatha ; Kashyap, Nachiketh V. ; Kulkarni, Varun P. et al. / Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm. ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings. editor / Thanikaiselvan V Thanikaiselvan V ; Renuga Devi S ; Shankar T ; Kalaivani S. Institute of Electrical and Electronics Engineers Inc., 2023. (ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings).

@inproceedings{17f24e7ad55c4fab8b47a093f0f32a4a,

title = "Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm",

abstract = "Breast cancer is a highly deadly and common cancer that is spreading over the world and claiming many lives. Breast cancer develops in the glandular tissue of the breast in the lining of epithelial cells of ducts or (15\%) lobules. These tissues heal with time. These in situ tumours may develop over time and infect the breast cells' immediate environs (stage 1), impact the lymph nodes, and finally totally spread throughout the body's organs (stage 3). There were 685,000 deaths worldwide in 2020 and a later rise in the number of malignant women. Cancer was a common disease that affected 7.8 million of the female population. The k-means algorithm is a popular data clustering algorithm. As the main analytical routine in data mining, the techniques of the clustering algorithm will impact the clustering outcome directly. This paper examines the shortcomings of the standard k-means algorithm and discusses them. This paper reviews existing methods for selecting the number of clusters for the algorithm. However, one of its drawbacks is the requirement that the number of clusters, K, be specified before the algorithm is applied. Therefore, we obtained an accuracy of 85\% after executing the program, and we were able to depict the difference between a benign and a malignant tumour. And we were able to see the centroid between the two tumours.",

author = "Soumyalatha Naveen and Kashyap, \{Nachiketh V.\} and Kulkarni, \{Varun P.\} and A. Sandeep and Chakradhar, \{Meruva Sai\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023 ; Conference date: 05-05-2023 Through 06-05-2023",

year = "2023",

doi = "10.1109/ViTECoN58111.2023.10157765",

language = "English",

series = "ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings",

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

editor = "\{Thanikaiselvan V\}, \{Thanikaiselvan V\} and S, \{Renuga Devi\} and Shankar T and Kalaivani S",

booktitle = "ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings",

address = "United States",

}

Naveen, S, Kashyap, NV, Kulkarni, VP, Sandeep, A & Chakradhar, MS 2023, Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm. in TV Thanikaiselvan V, RD S, S T & K S (eds), ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings. ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings, Institute of Electrical and Electronics Engineers Inc., 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023, Vellore, India, 05-05-23. https://doi.org/10.1109/ViTECoN58111.2023.10157765

Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm. / Naveen, Soumyalatha; Kashyap, Nachiketh V.; Kulkarni, Varun P. et al.
ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings. ed. / Thanikaiselvan V Thanikaiselvan V; Renuga Devi S; Shankar T; Kalaivani S. Institute of Electrical and Electronics Engineers Inc., 2023. (ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings).

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

TY - GEN

T1 - Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm

AU - Naveen, Soumyalatha

AU - Kashyap, Nachiketh V.

AU - Kulkarni, Varun P.

AU - Sandeep, A.

AU - Chakradhar, Meruva Sai

PY - 2023

Y1 - 2023

N2 - Breast cancer is a highly deadly and common cancer that is spreading over the world and claiming many lives. Breast cancer develops in the glandular tissue of the breast in the lining of epithelial cells of ducts or (15%) lobules. These tissues heal with time. These in situ tumours may develop over time and infect the breast cells' immediate environs (stage 1), impact the lymph nodes, and finally totally spread throughout the body's organs (stage 3). There were 685,000 deaths worldwide in 2020 and a later rise in the number of malignant women. Cancer was a common disease that affected 7.8 million of the female population. The k-means algorithm is a popular data clustering algorithm. As the main analytical routine in data mining, the techniques of the clustering algorithm will impact the clustering outcome directly. This paper examines the shortcomings of the standard k-means algorithm and discusses them. This paper reviews existing methods for selecting the number of clusters for the algorithm. However, one of its drawbacks is the requirement that the number of clusters, K, be specified before the algorithm is applied. Therefore, we obtained an accuracy of 85% after executing the program, and we were able to depict the difference between a benign and a malignant tumour. And we were able to see the centroid between the two tumours.

AB - Breast cancer is a highly deadly and common cancer that is spreading over the world and claiming many lives. Breast cancer develops in the glandular tissue of the breast in the lining of epithelial cells of ducts or (15%) lobules. These tissues heal with time. These in situ tumours may develop over time and infect the breast cells' immediate environs (stage 1), impact the lymph nodes, and finally totally spread throughout the body's organs (stage 3). There were 685,000 deaths worldwide in 2020 and a later rise in the number of malignant women. Cancer was a common disease that affected 7.8 million of the female population. The k-means algorithm is a popular data clustering algorithm. As the main analytical routine in data mining, the techniques of the clustering algorithm will impact the clustering outcome directly. This paper examines the shortcomings of the standard k-means algorithm and discusses them. This paper reviews existing methods for selecting the number of clusters for the algorithm. However, one of its drawbacks is the requirement that the number of clusters, K, be specified before the algorithm is applied. Therefore, we obtained an accuracy of 85% after executing the program, and we were able to depict the difference between a benign and a malignant tumour. And we were able to see the centroid between the two tumours.

UR - https://www.scopus.com/pages/publications/85165545584

UR - https://www.scopus.com/pages/publications/85165545584#tab=citedBy

U2 - 10.1109/ViTECoN58111.2023.10157765

DO - 10.1109/ViTECoN58111.2023.10157765

M3 - Conference contribution

AN - SCOPUS:85165545584

T3 - ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings

BT - ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings

A2 - Thanikaiselvan V, Thanikaiselvan V

A2 - S, Renuga Devi

A2 - T, Shankar

A2 - S, Kalaivani

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

Y2 - 5 May 2023 through 6 May 2023

ER -

Naveen S, Kashyap NV, Kulkarni VP, Sandeep A, Chakradhar MS. Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm. In Thanikaiselvan V TV, S RD, T S, S K, editors, ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings). doi: 10.1109/ViTECoN58111.2023.10157765

Breast Cancer Prediction Using Unsupervised Learning Technique K-Means Clustering Algorithm

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