Fuzzy Arithmetic–Based Algorithm for Identifying Medical Conditions for Better Treatment
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35-46
Digital Object Identifier:
10.58578/mjms.v1i1.2074
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Authors:Gyan Prasad Paudel1, Parbati Kumari Upadhyay2*, Aasis Baral3
Copyright :Authors retain copyright and grant the journal right of first publication.
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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.
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