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To model diverse real-world phenomena, a range of uncertainty-handling concepts has been actively studied, including Fuzzy Sets [1, 2], Rough Sets [3], Intuitionistic Fuzzy Sets [4], Paraconsistent Sets [5], Neutrosophic Sets [6, 7], Hyperneutrosophic Sets [8], Plithogenic Sets [9], and others. Among these extensions of fuzzy sets, Hyperfuzzy Sets are of particular significance. A hyperfuzzy set extends the notion of fuzzy sets to a hierarchical structure, enabling a more refined and flexible representation of uncertainty. In addition, the notion of a HyperRough Set generalizes the classical setting to multi-attribute data by assigning, to each attribute profile, a subset of the universe and then taking rough approximations with respect to a fixed indiscernibility relation. However, research on real-life applications of Hyperfuzzy Sets and HyperRough Sets remains limited. This paper explores application examples drawn from real-world scenarios by examining system integration using the Hyperfuzzy Set and HyperRough Set frameworks. Note that Health-Care system integration is the process of connecting distinct subsystems or components into a unified, functional, and efficient whole.
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