The week's pick
Reseach Article
Breast Cancer Detection using Machine Learning Techniques
| 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
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
- 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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- S. Laghmati, A. Tmiri and B. Cherradi, "Machine Learning based System for Prediction of Breast Cancer Severity," 2019 International Conference on Wireless Networks and Mobile Communications (WINCOM), 2019, pp. 1-5, doi: 10.1109/WINCOM47513.2019.8942575.
- M. Gupta and B. Gupta, "A Comparative Study of Breast Cancer Diagnosis Using Supervised Machine Learning Techniques," 2018 Second International Conference on Computing Methodologies and Communication (ICCMC), 2018, pp. 997-1002, doi: 10.1109/ICCMC.2018.8487537.
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