Fuzzy Arithmetic–Based Algorithm for Identifying Medical Conditions for Better Treatment

Page Numbers: 35-46
Published
2023-10-31
Digital Object Identifier: 10.58578/mjms.v1i1.2074
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  • Gyan Prasad Paudel Mid-West University, Surkhet, Nepal
  • Parbati Kumari Upadhyay Mid-West University, Surkhet, Nepal
  • Aasis Baral Mid-West University, Surkhet, Nepal

Abstract

Making the right medical decision is challenging work because, in our daily life, decision-making problems may have the components of membership and non-membership degrees with the possibility of hesitation. Since soft theory offers a theoretical framework for dealing with ambiguous, fuzzy, and ill-defined objects, it is a key development in the field of computer programming as well as other scientific disciplines. Intuitionistic fuzzy soft sets provide an effective tool for solving multiple attribute decision-making with intuitionistic fuzzy information. The most essential issue is how to derive the ranking of alternatives from the information quantified in terms of intuitional fuzzy values. This theory also has the potential to be used to solve such real-world problems. In this work, we explore how Sanchez's medical theory could be used in medical diagnosis and provide a fuzzy arithmetic-based algorithm for identifying medical conditions to address this.

Keywords: Fuzzy Logic; Inference System; Insurance; Index Of Vagueness; Claim Validation

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How to Cite
Paudel, G. P., Upadhyay, P. K., & Baral, A. (2023). Fuzzy Arithmetic–Based Algorithm for Identifying Medical Conditions for Better Treatment. Mikailalsys Journal of Mathematics and Statistics, 1(1), 35-46. https://doi.org/10.58578/mjms.v1i1.2074
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Vol 1 No 1 (2023): Mikailalsys Journal of Mathematics and Statistics
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Articles

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