Online sequential extreme learning machine approach for breast cancer diagnosis
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00521-024-09617-x.pdf
Reference73 articles.
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2. Albadr MA et al (2023) Breast cancer diagnosis using fast learning network algorithm. Front Oncol 13:1679
3. DeSantis CE et al (2019) Breast cancer statistics. CA: Cancer J Clin 69(6):438–451
4. Briguglio G et al (2020) Polyphenols in cancer prevention: New insights. Int J Funct Nutr 1(2):1–1
5. Dubey AK, Gupta U, Jain S (2015) A survey on breast cancer scenario and prediction strategy. In: Proceedings of the 3rd international conference on frontiers of intelligent computing: theory and applications (FICTA) 2014. Springer
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