Picture Similarity Measures and Their Application to Medical Diagnosis

Abstract

AbstractOne of the recent extensions of the ordinary fuzzy sets, picture fuzzy sets (PFS), is an effective tool to handle ambiguity and quantifying decision-maker evaluations. The idea behind PFS is to give decision-makers a more comprehensive range for defining membership, non-membership, and hesitancy degrees. The similarity measure is an essential and valuable tool for the degree of similarity between two objects. Many applications exist based on Jaccard, Dice, sin, and cosine similarity measures applying for medical diagnosis, pattern recognition, and network comparison in the literature. There is some developed similarity measures of PFS in the literature since they are limited compared to other extensions of fuzzy sets. In this study, the Jaccard similarity measure and weighted Jaccard similarity measure of picture fuzzy sets is presented. The newly defined similarity measures are employed for the medical diagnosis of the Coronavirus Disease (COVID-19) virus. In this application, the goal is to detect whether a patient is suffering from COVID-19 or not. The results are shared related to the Jaccard similarity measure, and some advantages of the proposed study are discussed.KeywordsPicture fuzzy setsSimilarity measuresJaccard similarityCOVID-19