An application of neutrosophic hypersoft mapping to diagnose brain tumor and propose appropriate treatment

Abstract

Brain tumors are one of the leading causes of death around the globe. More than 10 million people fall prey to it every year. This paper aims to characterize the discussions related to the diagnosis of tumors with their related problems. After examining the side effects of tumors, it encases similar indications, and it is hard to distinguish the precise type of tumors with their seriousness. Since in practical assessment, the indeterminacy and falsity parts are frequently dismissed, and because of this issue, it is hard to notice the precision in the patient’s progress history and cannot foresee the period of treatment. The Neutrosophic Hypersoft set (NHS) and the NHS mapping with its inverse mapping has been design to overcome this issue since it can deal with the parametric values of such disease in more detail considering the sub-parametric values; and their order and arrangement. These ideas are capable and essential to analyze the issue properly by interfacing it with scientific modeling. This investigation builds up a connection between symptoms and medicines, which diminishes the difficulty of the narrative. A table depending on a fuzzy interval between [0, 1] for the sorts of tumors is constructed. The calculation depends on NHS mapping to adequately recognize the disease and choose the best medication for each patient’s relating sickness. Finally, the generalized NHS mapping is presented, which will encourage a specialist to extricate the patient’s progress history and to foresee the time of treatment till the infection is relieved.

Aggregation Operators for Interval-Valued Pythagorean Fuzzy Hypersoft Set with Their Application to Solve MCDM Problem

“…Rahman et al [33] established a DM methodology for neutrosophic HSS. Saeed et al [34] utilized the neutrosophic hypersoft mapping to diagnose the brain tumor. Zulqarnain et al [35] extended the TOPSIS method based on the correlation coefficient for IFHSS and used it to resolve MADM complications.…”

An Integrated Algorithmic MADM Approach for Heart Diseases’ Diagnosis Based on Neutrosophic Hypersoft Set with Possibility Degree-Based Setting

“…They employed decision-making techniques such as TOPSIS to deal with real-world problems using the accuracy function. Saeed et al [ 18 , 19 ] introduced the concept of mappings under the NHs-set environment and applied them in decision-making for medical diagnosis. They [ 20 , 21 ] also discussed the representation of the NHs-set in graphs along with certain operations and products with application in decision-making.…”

A Novel Fuzzy Parameterized Fuzzy Hypersoft Set and Riesz Summability Approach Based Decision Support System for Diagnosis of Heart Diseases

“…They utilized algorithm-based techniques to resolve real-world DM issues. Saeed et al [ 24 , 25 , 26 , 27 , 28 , 29 ] characterized the novel notions of neutrosophic hypersoft mappings, complex multifuzzy -set, and neutrosophic hypersoft graphs with applications in decision-making and clinical diagnosis. Saqlain et al [ 30 , 31 , 32 ] discussed decision-making techniques for neutrosophic -set with the help of aggregation operators and accuracy functions.…”