Comprehensive Survey of Recent Applications of Q-Neutrosophic Soft Set in Medical Diagnosis System

Neutrosophic Soft Set (NSS) is one of the potential mathematical model for handling parametric uncertainties in dynamic environment. Q-NSS is extended version of NSS which incorporates the features of both NSS and Q-fuzzy set in handling uncertainty. Nowadays medical diagnosis system is prone to varieties of uncertainty in terms of uncertain disease symptoms, processing logic, and even uncertain clinical decisions. Handling the uncertainties is important before arriving at meaningful inferences. Hence in this chapter a comprehensive survey is carried out towards Q-NSS in all possible dimensions of medical diagnosis system. The survey highlights all possible mathematical frameworks used for medical diagnosis along with their limitations which include fuzzy logic, evidential reasoning, and quantum & machine learning decisions. The main focus of the paper is to perform early diagnosis of diseases, decision making under uncertainty, solutions for multi-attribute decision making problems, arriving at best decisions from several alternatives, and many more. A comparative analysis of Q-NSS is carried out with other mathematical frameworks like Neutrosophic Soft Set (NSS), and Q-Fuzzy set. It is inferred that the performance of Q-NSS is satisfactory towards performance metrics like error rate, throughput, latency, and resource utilization.