Classification of skin cancer stages using a AHP fuzzy technique within the context of big data healthcare.

Journal: Journal of cancer research and clinical oncology
Published Date: May 2, 2023

Abstract

BACKGROUND AND OBJECTIVES: Skin conditions in humans can be challenging to diagnose. Skin cancer manifests itself without warning. In the future, these illnesses, which have been an issue for many, will be identified and treated. With the rapid expansion of big data healthcare framework summarization and precise prediction in early stage skin cancer diagnosis, the fuzzy AHP technique produces the best results in both of these fields. Big data is a potent technology that enhances the standard of research and generates better results more rapidly. This essay gives a way to group the stages of skin cancer treatment based on this information. The combination of support vector machine multi-class classification and fuzzy selector with radial basis function-based binary migration classification of virtual machines is put through a number of experiments. The connections have been categorized.

Authors

  • Moslem Samiei
    Department of Industrial Engineering, Islamic Azad University, Zahedan Branch, Zahedan, Iran.
  • Alireza Hassani
    Center for Physics Technologies: Acoustics, Materials and Astrophysics, Department of Applied Physics, Universitat Politècnica de València, València, Spain.
  • Sliva Sarspy
    Department of Computer Science, College of Science, Cihan University-Erbil, Erbil, Iraq.
  • Iraj Elyasi Komari
    Department of Computer Engineering, Andimeshk Branch, Islamic Azad University, Andimeshk, Iran.
  • Mohammad Trik
    Department of Computer Engineering, Boukan Branch, Islamic Azad University, Boukan, Iran. trik.mohammad@gmail.com.
  • Foad Hassanpour
    Faculty of Information Technology and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.

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