Publication Date
4-1-2025
Abstract
In medicine, many diagnoses are made when, for some value k, at least k of n possible symptoms are present. Many of such symptoms -- such as fever -- are, in reality, fuzzy. For example, it makes no sense that say that 38.0 is fever while 37.9 is not a fever, both are fever to some degree. Once such degrees are given, we need to use them to estimate the degree to which the patient has the corresponding disease. For this problem, the usual fuzzy techniques require exponentially many computational steps -- so it is desirable to have a more efficient algorithm. Such an algorithm was previously proposed for some specific "and"-operation (t-norm). However, in different application areas, different "and"-operation describe the reasoning within this domain. So, it is desirable to extend the existing feasible algorithm to the case of general "and"-operations. In this paper, we describe such an extension.
Comments
Technical Report: UTEP-CS-25-13