Journal of Electronic Science and Technology, Volume. 23, Issue 2, 100315(2025)

Efficient feature selection based on Gower distance for breast cancer diagnosis

Salwa Shakir Baawi... Mustafa Noaman Kadhim* and Dhiah Al-Shammary |Show fewer author(s)
Author Affiliations
  • College of Computer Science and Information Technology, University of Al-Qadisiyah, Al Diwaniyah, 58001, Iraq
  • show less
    References(30)

    [1] [1] WHO, Breast Cancer [Online]. Available, https:www.who.intnewsroomfactsheetsdetailbreastcancer, November 2021.

    [2] Wang H.-Y., Feng J., Bu Q.-R. et al. Breast mass detection in digital mammogram based on Gestalt psychology. J. Healthc. Eng., 2018, 4015613(2018).

    [3] Valvano G., Santini G., Martini N. et al. Convolutional neural networks for the segmentation of microcalcification in mammography imaging. J. Healthc. Eng., 2019, 9360941(2019).

    [5] [5] M. Gupta, B. Gupta, A comparative study of breast cancer diagnosis using supervised machine learning techniques, in: Proc. of the 2nd Intl. Conf. on Computing Methodologies Communication, Erode, India, 2018, pp. 997–1002.

    [7] [7] P. Dinesh, A.S. Vickram, P. Kalyanasundaram, Medical image prediction f diagnosis of breast cancer disease comparing the machine learning algithms: SVM, KNN, logistic regression, rom fest decision tree to measure accuracy, AIP Conf. Proc. 2853 (1) (2024) 020140.

    [8] Putra L.G.R., Marzuki K., Hairani H.. Correlation-based feature selection and Smote-Tomek Link to improve the performance of machine learning methods on cancer disease prediction. Eng. Appl. Sci. Res., 50, 577-583(2023).

    [9] Maheswari B.U., Guhan T., Britto C.F., Sheeba A., Rajakumar M.P., Pratyush K.. Performance analysis of classifying the breast cancer images using KNN and naive Bayes classifier. AIP Conf. Proc., 2831, 020012(2023).

    [11] Laghmati S., Hamida S., Hicham K., Cherradi B., Tmiri A.. An improved breast cancer disease prediction system using ML and PCA. Multimed. Tools Appl., 83, 33785-33821(2024).

    [15] Singh L.K., Khanna M., Singh R.. Efficient feature selection for breast cancer classification using soft computing approach: a novel clinical decision support system. Multimed. Tools Appl., 83, 43223-43276(2024).

    [21] [21] S. Ara, A. Das, A. Dey, Malignant benign breast cancer classification using machine learning algithms, in: Proc. of the Intl. Conf. on Artificial Intelligence, Islamabad, Pakistan, 2021, pp. 97–101.

    Tools

    Get Citation

    Copy Citation Text

    Salwa Shakir Baawi, Mustafa Noaman Kadhim, Dhiah Al-Shammary. Efficient feature selection based on Gower distance for breast cancer diagnosis[J]. Journal of Electronic Science and Technology, 2025, 23(2): 100315

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Dec. 3, 2024

    Accepted: Apr. 21, 2025

    Published Online: Jun. 16, 2025

    The Author Email: Mustafa Noaman Kadhim (mustafa.noaman@qu.edu.iq)

    DOI:10.1016/j.jnlest.2025.100315

    Topics