Breast Cancer Prediction Model Using Machine Learning
Breast cancer requires early detection, hence it can be prevented earlier or treated more optimally. This article aims to demonstrate predictive modelling of breast cancer and evaluate the accuracy of its predictions using a machine learning approach. This study uses secondary data from the Wisconsi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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INTI International University
2021
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| Online Access: | http://eprints.intimal.edu.my/1525/ http://eprints.intimal.edu.my/1525/1/vol.2021_002.pdf |
| _version_ | 1848766761758883840 |
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| author | Muhammad Amin, Bakri Inna, Ekawati |
| author_facet | Muhammad Amin, Bakri Inna, Ekawati |
| author_sort | Muhammad Amin, Bakri |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | Breast cancer requires early detection, hence it can be prevented earlier or treated more optimally. This article aims to demonstrate predictive modelling of breast cancer and evaluate the accuracy of its predictions using a machine learning approach. This study uses secondary data from the Wisconsin Breast Cancer Dataset (BCWD) which consists of predictive factors for breast cancer and labels for benign or malignant cancers that result. Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. Evaluation of the classification performance of each algorithm is carried out by analysing its sensitivity, specificity, and accuracy. The experimental results show that Random Forest has better prediction accuracy (99.6%) followed by Support Vector Machine (98.7%), and Logistic Regression (93.9%). |
| first_indexed | 2025-11-14T11:56:17Z |
| format | Article |
| id | intimal-1525 |
| institution | INTI International University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:56:17Z |
| publishDate | 2021 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-15252021-08-26T10:26:27Z http://eprints.intimal.edu.my/1525/ Breast Cancer Prediction Model Using Machine Learning Muhammad Amin, Bakri Inna, Ekawati QA75 Electronic computers. Computer science QA76 Computer software Breast cancer requires early detection, hence it can be prevented earlier or treated more optimally. This article aims to demonstrate predictive modelling of breast cancer and evaluate the accuracy of its predictions using a machine learning approach. This study uses secondary data from the Wisconsin Breast Cancer Dataset (BCWD) which consists of predictive factors for breast cancer and labels for benign or malignant cancers that result. Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. Evaluation of the classification performance of each algorithm is carried out by analysing its sensitivity, specificity, and accuracy. The experimental results show that Random Forest has better prediction accuracy (99.6%) followed by Support Vector Machine (98.7%), and Logistic Regression (93.9%). INTI International University 2021-09 Article PeerReviewed text en http://eprints.intimal.edu.my/1525/1/vol.2021_002.pdf Muhammad Amin, Bakri and Inna, Ekawati (2021) Breast Cancer Prediction Model Using Machine Learning. Journal of Data Science, 2021 (02). ISSN 2805-5160 https://ipublishing.intimal.edu.my/jods.html |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software Muhammad Amin, Bakri Inna, Ekawati Breast Cancer Prediction Model Using Machine Learning |
| title | Breast Cancer Prediction Model Using Machine Learning |
| title_full | Breast Cancer Prediction Model Using Machine Learning |
| title_fullStr | Breast Cancer Prediction Model Using Machine Learning |
| title_full_unstemmed | Breast Cancer Prediction Model Using Machine Learning |
| title_short | Breast Cancer Prediction Model Using Machine Learning |
| title_sort | breast cancer prediction model using machine learning |
| topic | QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://eprints.intimal.edu.my/1525/ http://eprints.intimal.edu.my/1525/ http://eprints.intimal.edu.my/1525/1/vol.2021_002.pdf |