Author:
Sharma Piyush,Laxkar Pradeep,Kumar Anuj
Publisher
Springer Nature Singapore
Reference99 articles.
1. Wang, D., Khosla, A., Gargeya, R., Irshad, H., Beck, A.H.: Deep learning for identifying metastatic breast cancer. arXiv preprint arXiv:1606.05718 (2016)
2. Wang, J., Yang, X., Cai, H., Tan, W., Jin, C., Li, L.: Discrimination of breast cancer with microcalcifications on mammography by deep learning. Sci. Rep. 6(1), 1–9 (2016)
3. Nahid, A.A., Kong, Y.: Involvement of machine learning for breast cancer image classification: a survey Comput. Math. Methods Med. 2017, (2017). Article ID 3781951. https://doi.org/10.1155/2017/3781951
4. Fatima, N., Liu, L., Hong, S., Ahmed, H.: Prediction of breast cancer, comparative review of machine learning techniques, and their analysis. IEEE Access 8, 150360–150376 (2020)
5. Hou, R., et al.: Prediction of upstaged ductal carcinoma in situ using forced labeling and domain adaptation. IEEE Trans. Biomed. Eng. 67(6), 1565–1572 (2019)