Wan Zuki Azman Wan Muhamad
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Wan Zuki Azman Wan Muhamad
Official Name
Wan Zuki Azman, Wan Muhamad
Alternative Name
Azman, Wan Zuki
Wan Ahmad, Wan Zuki Azman
Muhamad, Wan Zuki Azmanwan
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Scopus Author ID
55860800560
Researcher ID
R-4128-2019

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Publication

Breast cancer status, grading system, etiology, and challenges in Asia: an updated review

2023 , Tan Xiao Jian , Cheor Wai Loon , Cheng Ee Meng , Khairul Shakir Ab Rahman , Wan Zuki Azman Wan Muhamad , Leow Wai Zhe

The number of breast cancer incidences reported worldwide has increased tremendously over the years. Scoping down to Asia, in 2020, the reported incidences of breast cancer are appalling, comprising 1,026,171 cases, occupying up to 45.4% of cases across the globe. Breast cancer is a non-communicable disease, that emerges in variegated forms, self-subsistent, and the etiology is observed to be multifactorial, dependent on the individual reproductive pattern, hormonal factors, diet, physical activity, lifestyle, and exposure to certain advent procedures. Given this complexity, breast cancer is expected to undergo a persistent increment in the number of incidences in near future, exacerbating the public health quality, regardless of race, ethnicity, geographical subgroups, and socioeconomic. In this review article, the authors examine breast cancer in multiple facets, comprising the updated statistics on breast cancer, typically in Asia; etiology of breast cancer; diagnosis of breast cancer; grading system; and challenges in breast cancer from the country’s income perspective. Realizing the ever-increasing demand for quality treatment, here, the article also contemplates common therapies in breast cancer, such as breast-conserving therapy, mastectomy, postmastectomy radiation therapy, neoadjuvant chemotherapy, axillary surgery, chemotherapy, adjuvant medical therapies, biological and targeted therapies, and endocrine therapy. This review article intended to provide a brief yet broad panoramic view of breast cancer, to readers, ranging from newcomers, existing researchers, and relevant stakeholders in the topic of interest.

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Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset

2023 , Chow Yong Huan , Wan Zuki Azman Wan Muhamad , Zainor Ridzuan Yahya , Nor Hizamiyani Abdul Azziz , Tan Chye Lih , Tan Xiao Jian

The Mahalanobis-Taguchi System (MTS) is a statistical approach used in breast cancer research to facilitate early detection and promote efficient treatment. The technique analyses mammogram images for significant features using a multivariate statistical analysis technique. It combines the Mahalanobis distance (MD) and Taguchi's method to determine the differences between benign and malignant samples. While orthogonal array (OA) has been widely used in MTS, it has been criticised for providing suboptimal results due to insufficient coverage of feature combinations during the feature optimisation process. To address this issue, the Binary Whale Optimisation Algorithm (BWOA) is proposed as an improved search algorithm for MTS. This paper aims to develop a novel hybrid method that enhances the efficiency of the Mahalanobis Taguchi System (MTS). The performance of feature selection ability due to different MTS hybrid algorithms were also compared. BWOA simulates the hunting behaviour of humpback whales and works by exploring new regions of the solution space, gradually narrowing the search space, and fine-tuning the solution. MTS-BWOA demonstrated its enhanced capability in feature optimisation compared to traditional MTS methods and has the potential to be applied in other medical imaging domains.

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