Medical diagnoses using three-way fuzzy concept lattice and their Euclidean distance

摘要: Searching the closest symptoms of a particular disease in given patient is major concern for medical diagnoses expert. In most cases, this problem arises due to large number incomplete, uncertain, or inconsistent information generated data set. Recently, some researchers tried pay attention towards precise measurement uncertainty and vagueness set using properties applied abstract algebra. process, noticed that calculus three-way decision space more useful characterize based on truth, indeterminacy, falsity membership-values. However, searching relevant query user requirement issue space. To encounter problem, current paper analyze single-valued neutrosophic graph-based concept lattice. addition, another method proposed select interesting fuzzy concepts at user-defined granulation their computed Euclidean distance with an illustrative example.