Leow Wai Zhe
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Preferred name
Leow Wai Zhe
Official Name
Wai Zhe, Leow
Alternative Name
Leow, Wai Zhe
Leow, W. Z.
Zhe, Leow Wai
Zhe, L. W.
Main Affiliation
Scopus Author ID
56178375200
Researcher ID
DXJ-9302-2022

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  • Publication
    Breast cancer status, grading system, etiology, and challenges in Asia: an updated review
    (De Gruyter Brill, 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.
      1  2
  • Publication
    Assessment of wind power potential in the North region of Malaysia, Chuping Perlis
    ( 2023-01-01)
    Thiraphorn Bun Leew
    ;
    Leow Wai Zhe
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Tan Xiao Jian
    ;
    Muhammad Irwanto Misrun
    ;
    Kumuthawathe Ananda-Rao
    The wind turbines is a main device that convert the kinetic energy from blades to electrical energy. Before installing wind turbines, the Weibull probability distribution must be calculated to determine the certain wind speed probability. Many problems will come if there no analysis the characteristics of wind in selected location, such as wind speed that not suitable for building wind farm to supply the population in that area. Shape and scale factors, which be controlled in a variety of ways, influence the Weibull distribution. Many studies have looked into which of the various Weibull parameter estimation methods is the most dependable. However, because the results of these investigations were inconsistent, research into more trustworthy Weibull parameter estimation methods is still ongoing. An analysis of data collected Chuping, Perlis for two years was conducted in this study (from 2018 to 2019). By using statistical analysis to evaluate the Weibull distribution method, this study used three methods to compared the Weibull parameters and identified the most reliable and effective method to obtain the Weibull probability distribution by using a three approach that compares the variances of RMSE, MSE and R2, which provides comprehensive insight into level error and volatility. Modified maximum likelihood method, graphical method, and power density method are the three methods used in this study. Therefore, the graphical method has the best accuracy in the wind speed distribution prediction, several methods such as the modified maximum likelihood method, and the power density method have the worst prediction of the wind speed distribution based on all the statistical method variances for this region.
      7  29