Hybrid PSO feature selection-based association classification approach for breast cancer detection-Reference-Cited by-同舟云学术

Hybrid PSO feature selection-based association classification approach for breast cancer detection

Published:2022-11-02 Issue:7 Volume:35 Page:5291-5317
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Sowan Bilal^ORCID,Eshtay Mohammed,Dahal Keshav,Qattous Hazem,Zhang Li

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-07950-7.pdf

Reference51 articles.

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2. Biblowit MJ (2022) Resources: breast cancer statistics and resources. https://www.bcrf.org/breast-cancer-statistics-and-resources. Accessed 1 Feb 2022

3. Wang S, Wang Y, Wang D, Yin Y, Wang Y, Jin Y (2020) An improved random forest-based rule extraction method for breast cancer diagnosis. Appl Soft Comput 86:105941

4. Alwidian J, Hammo BH, Obeid N (2018) WCBA: weighted classification based on association rules algorithm for breast cancer disease. Appl Soft Comput 62:536–549

5. Sowan B (2017) A comparative analysis of exam timetable using data mining techniques. IJCSNS 17(1):73

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