Abstract
Cancer deaths are one of the highest rates of death. Although breast cancer is commonly associated with women, it is sometimes seen in men, and the mortality rate for men with breast cancer may be higher. The importance of early detection and treatment of breast cancer cannot be overstated. Cancer is diagnosed at an early stage thanks to expert systems, artificial intelligence, and machine learning approaches, and data analysis makes life easier for healthcare professionals. The nearest neighbor method, principal component analysis, neighborhood component method approaches were employed to detect breast cancer in this study. "Breast Cancer Wisconsin Diagnostic" database was used to create and test the approach. According to the results obtained, the highest success rate with 99.42% was obtained by using neighborhood component analysis and nearest neighbor classification algorithm method.
Publisher
Bitlis Eren Universitesi Fen Bilimleri Dergisi
Reference21 articles.
1. 1. World Health Organzation, 2020, International Agency for Research on Cancer-IARC, dowload: https://gco.iarc.fr/today/home.
2. 2. Çelik, L., 2020, Meme Kanseri Taramasında Yapay Zeka, download:https://www.drozdogan.com/turkiye-kanser-istatistikleri-2020/
3. 3. Eyupoglu, C. (2018). Breast cancer classification using k-nearest neighbors algorithm. The Online Journal of Science and Technology, 8(3), 29-34.
4. 4. Jeleń, Ł., Krzyżak, A., Fevens, T., & Jeleń, M. (2016). Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies. Computers in Biology and Medicine, 79, 80- 91, doi: 10.1016/j.compbiomed.2016.10.007
5. 5. Gupta P., Garg S. (2020). Breast Cancer Prediction using varying Parameters of Machine Learning Models. Procedia Computer Science, vol. 171, pp. 593–601, doi: 10.1016/j.procs.2020.04.064.