Medical diagnostic process based on modified composite relation on pythagorean fuzzy multi-sets

Pythagorean fuzzy multiset (PFMS) is a generalized Pythagorean fuzzy set (PFS) with a higher degree of accuracy. It is characterized by the capacity to handle imprecisions because of its inbuilt ability to allow repetitions of the orthodox parameters of PFSs. Max–min–max composite relation on PFMSs has been studied and proven to be resourceful. However, max–min–max approach used maximum and minimum values of the parameters of PFMS only without considering the average values. This paper proposes a modified version of the max–min–max composite relation on PFMSs to enhance reliable output by incorporating the average values of the PFMSs’ parameters. Some numerical examples are given to juxtapose the correctness of the max–min–max composite relation on PFMSs with that of the modified version to ascertain reliability/superiority of the modified version. To demonstrate the applicability of the proposed composite relation on PFMSs, an illustration of medical diagnosis is considered assuming there are some patients whose symptoms are represented in Pythagorean fuzzy multi-values. To determine the diagnosis of the patients, the max–min–max composite relation and its modified version are deployed to find the correlation between each of the patients with some suspected diseases.