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20 December 2024
Reseach Article

Breast Cancer Detection using Machine Learning Techniques

by Md. Samiul Islam, Md. Ashikuzzaman, Joy Mojumdar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 39
Year of Publication: 2022
Authors: Md. Samiul Islam, Md. Ashikuzzaman, Joy Mojumdar
10.5120/ijca2022922490

Md. Samiul Islam, Md. Ashikuzzaman, Joy Mojumdar . Breast Cancer Detection using Machine Learning Techniques. International Journal of Computer Applications. 184, 39 ( Dec 2022), 13-19. DOI=10.5120/ijca2022922490

@article{ 10.5120/ijca2022922490,
author = { Md. Samiul Islam, Md. Ashikuzzaman, Joy Mojumdar },
title = { Breast Cancer Detection using Machine Learning Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2022 },
volume = { 184 },
number = { 39 },
month = { Dec },
year = { 2022 },
issn = { 0975-8887 },
pages = { 13-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number39/32570-2022922490/ },
doi = { 10.5120/ijca2022922490 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:33.647893+05:30
%A Md. Samiul Islam
%A Md. Ashikuzzaman
%A Joy Mojumdar
%T Breast Cancer Detection using Machine Learning Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 39
%P 13-19
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

According to the World Health Organization (WHO), in 2020, around 2.3 million women diagnosed with breast cancer, and 685,000 of them died globally. Though, this calculation is terrible to think, there is always a hope for the patients who are able to be diagnosed at the very early stage. Keeping this helpfulness of early diagnosis in mind, there have been proposed a lot of research works in the recent years. And, most of these researches are computer aided. This is the reason, in the recent years, machine learning techniques are getting quite noticed because of their efficiency and reliability. In this paper,6 different machine learning techniques such as Logistic Regression, Decision Tree Classifier, KNN (K-Nearest Neighbors), Random Forest Classifier, SVM (Support Vector Machine), and Gradient Boosting Classifier have been proposed to detect breast cancer.The very popular Breast Cancer Wisconsin (Original) Dataset [1] collected from UCI machine learning repository has been used to apply the proposed machine learning techniques. In this research work, 20% of data has been used for testing and the rest 80% of data has been used for training. Decision Tree Classifier outperformed the other techniques giving the highest accuracy of 96.89%. The results of other techniques were quite competitive.

References
  1. Breast Cancer Wisconsin (Original)Dataset collected from UCI machine learning repositorycreated by Dr. William H. Wolberg (physician) at the University of Wisconsin Hospitals, Madison, Wisconsin, USA. https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+%28original%29
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Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning Logistic Regression Decision Tree Classifier KNN (K-Nearest Neighbors) Random Forest Classifier SVM (Support Vector Machine) Gradient Boosting Classifier.