Enhancing Diabetes Diagnosis through an Intuitionistic Fuzzy Soft Matrices-Based Algorithm
DOI:
https://doi.org/10.31181/sems1120238uKeywords:
Decision-Making, Soft Set, IFS, IFSMs, Complement of IFSMs, Product of the IFSMAbstract
The diagnosis of Type-1 diabetes is a challenging and sophisticated procedure for medical experts. The complexity of this condition necessitates the use of sophisticated decision-making tools, and in this setting, intuitionistic soft set theory and its accompanying matrices prove to be invaluable resources. Our suggested technique uses intuitionistic soft matrices to solve challenging multi-criteria decision-making issues, opening a promising new direction for improving the precision of diabetes diagnosis. Diabetes requires careful evaluation and assessment since it is characterized by several illnesses that interfere with the body's capacity to control blood plasma glucose levels. Our main goal is to use intuitionistic fuzzy soft matrices to thoroughly examine diabetic patients in the decision-making domain. By giving medical professionals more accurate tools to treat this pervasive and difficult health issue, this novel strategy has the potential to revolutionize the diagnosis and management of diabetes.
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