Proposing an integrated method based on fuzzy tuning and ICA techniques to identify the most influencing features in breast cancer
Joint Authors
Masoudiasl, Irvan
Vahdat, Shaghayeh
Husam, Sumayyah
Shamshirb, Shihab al-Din
Alinejad Rokny, Hamid
Source
Iranian Red Crescent Medical Journal
Issue
Vol. 21, Issue 9 (30 Sep. 2019), pp.1-11, 11 p.
Publisher
Publication Date
2019-09-30
Country of Publication
United Arab Emirates
No. of Pages
11
Main Subjects
Topics
Abstract EN
Background: Breast cancer is the most common cancer in women, which has not been completely cured yet.
The traditional approaches have low accuracy for breast cancer detection.
However, intelligent techniques have been recently used in medical research to distinguish infected individuals from healthy ones, accurately.
Objectives: In this study, we aim to develop an ensemble machine learning (ML) method to distinguish tumor samples from healthy samples robustly.
Methods: We used an Imperial Competitive Algorithm coupled with a Fuzzy System (ICA-Fuzzy-SR) to identify the most influencing features to recognize tumor samples.
To evaluate the proposed method, we used the publicly available Wisconsin Breast Cancer Dataset (WBCD).
Results: Benchmarking with the current existing leading methods indicates that our proposed method achieves 95.45% prediction accuracy, which is 3% better than those reported in previous studies.
Conclusions: Such results achieve while our model is significantly faster than previously proposed models to solve this problem.
American Psychological Association (APA)
Masoudiasl, Irvan& Vahdat, Shaghayeh& Husam, Sumayyah& Shamshirb, Shihab al-Din& Alinejad Rokny, Hamid. 2019. Proposing an integrated method based on fuzzy tuning and ICA techniques to identify the most influencing features in breast cancer. Iranian Red Crescent Medical Journal،Vol. 21, no. 9, pp.1-11.
https://search.emarefa.net/detail/BIM-898345
Modern Language Association (MLA)
Masoudiasl, Irvan…[et al.]. Proposing an integrated method based on fuzzy tuning and ICA techniques to identify the most influencing features in breast cancer. Iranian Red Crescent Medical Journal Vol. 21, no. 9 (Sep. 2019), pp.1-11.
https://search.emarefa.net/detail/BIM-898345
American Medical Association (AMA)
Masoudiasl, Irvan& Vahdat, Shaghayeh& Husam, Sumayyah& Shamshirb, Shihab al-Din& Alinejad Rokny, Hamid. Proposing an integrated method based on fuzzy tuning and ICA techniques to identify the most influencing features in breast cancer. Iranian Red Crescent Medical Journal. 2019. Vol. 21, no. 9, pp.1-11.
https://search.emarefa.net/detail/BIM-898345
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 10-11
Record ID
BIM-898345