Adjustment of the Height Triangular Fuzzy Regression as Early Awareness of Breast Cancer

Breast cancer is the most popular malignancy among Malaysian women. In Malaysia, approximately one in every 19 women is at risk. Breast cancer is the most common cancer among Malaysian women (32.9%), followed by colorectal (11.9%) and ovarian cancers (7.2%). Many cases are found to be advanced, with considerable tumour development or metastasis to untreatable locations and unaware of the factors. This study aims to determine the best height triangular fuzzy regression model by adjustment between 0 – 1 and measure the value of statistical error using mean square error (MSE) and root mean square error (RMSE). Secondary data was used where 569 patients having BREAST cancer and receiving treatment in hospitals was recorded by nurses and doctors. The patient data for breast cancer were analysed using MATLAB, SPSS, and Microsoft Excel. Based on the results, H = 0 of fuzzy linear regression is the best model to predict the breast cancer awareness with lowest value of MSE and RMSE by 1.455 and 1.206 respectively. Malaysians must be aware of the warning factors of breast cancer to increase survival and minimise death rates.

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Publication Details

Journal
Journal of Advanced Research in Applied Sciences and Engineering Technology
Published
2024-09-21
DOI
https://doi.org/10.37934/araset.52.2.189197
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Adjustment of the Height Triangular Fuzzy Regression as Early Awareness of Breast Cancer

Mohd Saifullah Rusiman, Muhammad Ammar Shafi, Efendi Nasıbov, Suraya Othman et al.
Journal of Advanced Research in Applied Sciences and Engineering Technology
AI in cancer detection
article

Adjustment of the Height Triangular Fuzzy Regression as Early Awareness of Breast Cancer

Mohd Saifullah Rusiman, Muhammad Ammar Shafi, Efendi Nasıbov, Suraya Othman, Nor Faezan Abdul Rashid, Zulfana Lidinillah
article en

Abstract

Breast cancer is the most popular malignancy among Malaysian women. In Malaysia, approximately one in every 19 women is at risk. Breast cancer is the most common cancer among Malaysian women (32.9%), followed by colorectal (11.9%) and ovarian cancers (7.2%). Many cases are found to be advanced, with considerable tumour development or metastasis to untreatable locations and unaware of the factors. This study aims to determine the best height triangular fuzzy regression model by adjustment between 0 – 1 and measure the value of statistical error using mean square error (MSE) and root mean square error (RMSE). Secondary data was used where 569 patients having BREAST cancer and receiving treatment in hospitals was recorded by nurses and doctors. The patient data for breast cancer were analysed using MATLAB, SPSS, and Microsoft Excel. Based on the results, H = 0 of fuzzy linear regression is the best model to predict the breast cancer awareness with lowest value of MSE and RMSE by 1.455 and 1.206 respectively. Malaysians must be aware of the warning factors of breast cancer to increase survival and minimise death rates.

Journal of Advanced Research in Applied Sciences and Engineering Technology
Dokuz Eylül University (TR), Universiti Teknologi MARA (MY), Tun Hussein Onn University of Malaysia (MY)
Universiti Tun Hussein Onn Malaysia
Openalex Percentile: Top 86%
AI in cancer detection
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Adjustment of the Height Triangular Fuzzy Regression as Early Awareness of Breast Cancer — Mohd Saifullah Rusiman, Muhammad Ammar Shafi, et al. · Journal of Advanced Research in Applied Sciences and Engineering Technology (2024) | TGRS Research Map | TGRS