Multidimensional fuzzy norms and cut sets in the context of medical decision making

Abstract

This study introduces the concepts of complements, t-norms, t-conorms, and cut sets in the context of multi-dimensional fuzzy sets. Some fundamental results including DeMorgan-type identities, concerning these, are obtained. The advantage of using multidimensional fuzzy sets for analyzing data is that each element in the universe can be given individual attention as per the requirement. By utilizing this scope, as an application of the introduced concepts, stage identification of certain diseases based on Multidimensional fuzzy sets and intuitionistic fuzzy sets is provided together with a comparative study on typical biomedical data.