UWB-based early breast cancer existence prediction using artificial intelligence for large data set
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 th...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Penerbit Akademia Baru
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/38245/ http://umpir.ump.edu.my/id/eprint/38245/1/UWB-Based%20early%20breast%20cancer%20existence%20predictiont.pdf |
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| author | Ahmad Ashraf, Abdul Halim Veeraperumal, Vijayasarveswari Andrew, Allan Melvin Mohd Najib, Mohd Yasin Mohd Zamri Zahir, Ahmad Hossain, Kabir Bari, Bifta Sama Fatinnabila, Kamal |
| author_facet | Ahmad Ashraf, Abdul Halim Veeraperumal, Vijayasarveswari Andrew, Allan Melvin Mohd Najib, Mohd Yasin Mohd Zamri Zahir, Ahmad Hossain, Kabir Bari, Bifta Sama Fatinnabila, Kamal |
| author_sort | Ahmad Ashraf, Abdul Halim |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T03:29:15Z |
| format | Article |
| id | ump-38245 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:29:15Z |
| publishDate | 2023 |
| publisher | Penerbit Akademia Baru |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-382452023-09-05T07:32:00Z http://umpir.ump.edu.my/id/eprint/38245/ UWB-based early breast cancer existence prediction using artificial intelligence for large data set Ahmad Ashraf, Abdul Halim Veeraperumal, Vijayasarveswari Andrew, Allan Melvin Mohd Najib, Mohd Yasin Mohd Zamri Zahir, Ahmad Hossain, Kabir Bari, Bifta Sama Fatinnabila, Kamal T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering 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. Penerbit Akademia Baru 2023-01 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/38245/1/UWB-Based%20early%20breast%20cancer%20existence%20predictiont.pdf 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) https://doi.org/10.37934/araset.29.2.8190 https://doi.org/10.37934/araset.29.2.8190 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Ahmad Ashraf, Abdul Halim Veeraperumal, Vijayasarveswari Andrew, Allan Melvin Mohd Najib, Mohd Yasin Mohd Zamri Zahir, Ahmad Hossain, Kabir Bari, Bifta Sama Fatinnabila, Kamal UWB-based early breast cancer existence prediction using artificial intelligence for large data set |
| title | UWB-based early breast cancer existence prediction using artificial intelligence for large data set |
| title_full | UWB-based early breast cancer existence prediction using artificial intelligence for large data set |
| title_fullStr | UWB-based early breast cancer existence prediction using artificial intelligence for large data set |
| title_full_unstemmed | UWB-based early breast cancer existence prediction using artificial intelligence for large data set |
| title_short | UWB-based early breast cancer existence prediction using artificial intelligence for large data set |
| title_sort | uwb-based early breast cancer existence prediction using artificial intelligence for large data set |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/38245/ http://umpir.ump.edu.my/id/eprint/38245/ http://umpir.ump.edu.my/id/eprint/38245/ http://umpir.ump.edu.my/id/eprint/38245/1/UWB-Based%20early%20breast%20cancer%20existence%20predictiont.pdf |