Big data simulation software for breast cancer growth repository system

  • Authors

    • Norma Alias Universiti Teknologi Malaysia
    • Asnida Che. Abd. Ghani
    • Hafizah Farhah Saipan Saipo
    • Waleed Mugahed Al-Rahmi
    • Noraffandy Yahaya
    2018-10-06
    https://doi.org/10.14419/ijet.v7i4.15155
  • Breast Cancer Growth, Simulation Software Development, Repository Library, Numerical Methods, Helmholtz Equation

  • The development of the simulation software aims at anticipating the growth of breast cancer. Based on certain numerical iterative methods, this simulation works with discretization and Partial Differential Equation (PDE). As a class of Helmholtz equations, PDE approach are known to govern the growth of this type of cancer. Considering both time and place, the Helmholtz equation’s accuracy visualizes breast cancer and its growth. This growth is of breast cancer is captured and the convergence results in sequential and parallel computing environ-ment is expressed through the numerical libraries available in the repository system. Currently, both the parallel performance measurement and Numerical analysis that involve execution time, speedup, efficiency, effectiveness and temporal performance are being investigated. The process of breast cancer visualization requires a huge memory and expensive calculations. It is observed that both the distributed memory and distributed processors of the parallel computer systems development were required in most of the studies conducted on the growth of this cancer. It is considered as an important computation platform needed to the development of parallel repository system leading to an increase in the speed and a decrease in the cost. The simulation software has several beneficial characteristics such as high performance estimation, multidimensional visualization of breast cancer and being friendly. It also provides a real time solution and strength. This soft-ware is expected to increase the level of confidence in terms of computer-aided decision making which can be reflected positively on com-prehensive breast cancer screening; breast cancer diagnosis; and clinical assessments and treatment.

     

     

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  • How to Cite

    Alias, N., Che. Abd. Ghani, A., Farhah Saipan Saipo, H., Mugahed Al-Rahmi, W., & Yahaya, N. (2018). Big data simulation software for breast cancer growth repository system. International Journal of Engineering & Technology, 7(4), 2856-2861. https://doi.org/10.14419/ijet.v7i4.15155