Visitors: 1383

  MAZEDAN DIGITAL LIBRARY    

  JOURNAL MANAGEMENT SYSTEM

MDL
JMS  
MAZEDAN DIGITAL LIBRARY

Breast Cancer Classification using Multiple Machine Learning Techniques

JOURNAL:MAZEDAN COMPUTER ENGINEERING TRANSACTIONS

Download pdf
# Authors First Online DOI Downloads Citations
1. Vaishnawi Priyadarshni*, Sanjay Kumar Sharma 21 Dec 2021 MCET0202001 2 0
Abstract

Breast cancer (BC) is one of the most frequent cancers in women around the world, accounting for the majority of new cases and cancer-related deaths. It is a form of cancer that develops in the breast cells and may grow as a result of irregular cell division in the breast, resulting in a tumor that can be diagnosed and detected early, resulting in an increase in prognosis and chances of survival. It can also help patients receive better health care. Early cancer detection may save a patient's life. this paper, a comparison between multiple machine learning algorithms: Support Vector Machine, Decision Tree and Multi-Layer Perceptron. Support Vector Machine Provide better results than Multi-Layer Perception and Decision Tree. Support Vector Machine provides 95 % accuracy.

Keywords

Machine Learning, Support Vector Machine, Decision Tree, Multi-Layer perceptron, Breast Cancer

References

  1. [1]    Mangasarian, O. L., Street, W. N., & Wolberg, W. H. (1995). Breast cancer diagnosis and prognosis via linear programming. Operations Research, 43(4), 570-577.

    [2]    Lundin, M., Lundin, J., Burke, H. B., Toikkanen, S., Pylkkänen, L., & Joensuu, H. (1999). Artificial neural networks applied to survival prediction in breast cancer. Oncology, 57(4), 281-286.

    [3]    Vacek, P. M., Geller, B. M., Weaver, D. L., & Foster Jr, R. S. (2002). Increased mammography use and its impact on earlier breast cancer detection in Vermont, 1975–1999. Cancer, 94(8), 2160-2168.

    [4]    Brown, M. L., Houn, F., Sickles, E. A., & Kessler, L. G. (1995). Screening mammography in community practice: positive predictive value of abnormal findings and yield of follow-up diagnostic procedures. AJR. American journal of roentgenology, 165(6), 1373-1377.