UWB-based early breast cancer existence prediction using artificial intelligence for large data set

Ahmad Ashraf, Abdul Halim and Veeraperumal, Vijayasarveswari and Andrew, Allan Melvin and Mohd Najib, Mohd Yasin and Mohd Zamri Zahir, Ahmad and Hossain, Kabir and Bari, Bifta Sama and Fatinnabila, Kamal (2023) UWB-based early breast cancer existence prediction using artificial intelligence for large data set. Journal of Advanced Research in Applied Sciences and Engineering Technology, 29 (2). pp. 81-90. ISSN 2462-1943. (Published)

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Breast cancer is the most often identified cancer among women and the main reason for cancer-related deaths worldwide. The most effective methods for controlling and treating this disease through breast screening and emerging detection techniques. This paper proposes an intelligent classifier for the early detection of breast cancer using a larger dataset since there is limited researcher focus on that for better analytic models. To ensure that the issue is tackled, this project proposes an intelligent classifier using the Probabilistic Neural Network (PNN) with a statistical feature model that uses a more significant size of data set to analyze the prediction of the presence of breast cancer using Ultra Wideband (UWB). The proposed method is able to detect breast cancer existence with an average accuracy of 98.67%. The proposed module might become a potential user-friendly technology for early breast cancer detection in domestic use.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Breast cancer detection; Feature selection; Machine learning
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Institute of Postgraduate Studies
College of Engineering
Faculty of Electrical and Electronic Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 05 Sep 2023 07:32
Last Modified: 05 Sep 2023 07:32
URI: http://umpir.ump.edu.my/id/eprint/38245
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