Breast Cancer Classification Using Support Vector Machines (SVM)
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43056-5_16
Reference16 articles.
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2. Bustan, M.N., Poerwanto, B.: To cite this article: Kumar Sanjeev Priyanka. IOP Conf. Ser. Mater. Sci. Eng. 1022, 12071 (2021). https://doi.org/10.1088/1757-899X/1022/1/012071
3. Chang, W.T., Chen, P.W., Lin, H.W., Kuo, Y.H., Lin, S.H., Li, Y.H.: Risks of aromatase inhibitor-related cardiotoxicity in patients with breast cancer in Asia. Cancers 14, 508 (2022). https://doi.org/10.3390/CANCERS14030508/S1
4. Chaurasia, V., Pal, S.: A novel approach for breast cancer detection using data mining techniques (2017). https://papers.ssrn.com/abstract=2994932
5. Li, N., et al.: Global burden of breast cancer and attributable risk factors in 195 countries and territories, from 1990 to 2017: results from the global burden of disease study 2017. J. Hematol. Oncol. 12, 1–12 (2019). https://doi.org/10.1186/S13045-019-0828-0/FIGURES/6
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