Open Access

ARTICLE

Multi Criteria Decision Making for Evaluation and Ranking of Cancer Information

Shahid Mahmood^1,*, Muhammad Amin², Mubashir Baig Mirza¹, Salem Abu-Ghumsan¹, Muhammad Akram³, Zahid Mahmood Janjua⁴, Arslan Shahid⁵, Usman Shahid⁶

1 College of Dentistry, Prince Sattam Bin Abdulaziz University, Alkharj, 11942, Saudi Arabia
2 Department of Avionics Engineering, Institute of Space Technology, Islamabad, Pakistan
3 University of Engineering & Technology, Lahore, 56000, Pakistan
4 Systems International, Lahore, 56000, Pakistan
5 Arif Memorial Hospital, Lahore, 56000, Pakistan
6 University of Central Punjab, Lahore, 56000, Pakistan

* Corresponding Author: Shahid Mahmood. Email:

Computers, Materials & Continua 2023, 74(2), 4469-4481. https://doi.org/10.32604/cmc.2023.030728

Received 31 March 2022; Accepted 16 June 2022; Issue published 31 October 2022

Abstract

Cancer is a disease that is rapidly expanding in prevalence all over the world. Cancer cells can metastasize, or spread, across the body and impact several different cell types. Additionally, the incidence rates of several subtypes of cancer have been on the rise in India. The countermeasures for the cancer disease can be taken by determining the specific expansion rate of each type. To rank the various forms of cancer’s rate of progression, we used some of the available data. Numerous studies are available in the literature which show the growth rate of cancer by different techniques. The accuracy of the scheme in determining the highest growth rate may vary due to the variation in the dependent factors. Within the context of this research, the Fuzzy triangular technique for order preference by similarity to ideal solution (TOPSIS), is utilized to rank the various categorizations of cancer with the help of four groups of medical professionals acting in the capacity of decision-makers. The number of decision-makers may variate according to the required accuracy of results. The findings of the three-dimensional Fuzzy TOPSIS analysis categorize each variety of cancer according to the rate at which it spreads over time. Numerical results along with visual representation are presented to examine the efficiency of our proposed work.

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Keywords

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