A Medical Diagnosis Based on Interval-Valued Fuzzy Sets

Abstract

In this paper, we propose a fuzzy diagnostic method based on interval-valued intuitionistic fuzzy sets. For this purpose, we developed an interval-valued interview chart with interval fuzzy degree assigned to the relation among symptoms and diseases, and utilized the interval-valued intuitionistic fuzzy weighted arithmetic average operator to aggregate fuzzy information from the symptoms. In addition, we suggest a diagnosis measure using the occurrence proportion of patient's symptoms. Finally, an illustrative example is given to demonstrate its practicality and effectiveness.

A Historical Account of Types of Fuzzy Sets and Their Relationships

“…For some decision making problems, the use of IVFSs allows to choose a solution when FSs fail to do so [36]. Finally, IVFSs have also been used successfully in web problems [86], pattern recognition [39], medicine [40], etc. see also [97], [149].…”

On Γ-Interval Valued Fuzzification of Lagrange’s Theorem of Γ-Interval Valued Fuzzy Subgroups

“…For more recent development in IVFSs, we refer to [24]- [26]. In 2012, a fuzzy diagnostic method based on IV intuitionistic fuzzy sets was recommended by Choi et al [27]. Ahn et al [28] presented an important application of this phenomenon in the medical diagnosis of headache.…”

Width-Based Interval-Valued Distances and Fuzzy Entropies

“…Distance measures and entropies are significant notions in fuzzy sets theory due to their high applicability [18], [26], [29], [31], [35], [43], [45]. At the same time, interval-valued fuzzy sets [12] in many cases improve the results of fuzzy sets in different applications [1]- [4], [6], [7], [11], [14], [16], [17], [22], [34], [42], since they allow us to take into account the uncertainty linked to the construction of a precise membership function. For this reason, there exists a wide interest in the literature for extending the notions of distance measure and entropy to deal with interval-valued fuzzy sets and entropies [5], [23], [37], [38].…”