Prediction of Schizophrenia in Patients Using Fuzzy AHP and TOPSIS Methods

会议论文
发表日期：

2024年

查看全文

R. Anoop,
Impana Anand,
Mohammed Rehan,
R. Yashvanth,
Ashwini Kodipalli,
Trupthi Rao,
Shoaib Kamal

摘要

Schizophrenia is a chronic illness that most frequently affects people between the ages of 16 and 30. There are many elements that lead to a patient receiving a diagnosis of the illness, but since the origin of the illness is unknown, fuzzy analysis can be an important tool in identifying the factors. The purpose of this study report is to inform readers of the factors that have the greatest influence on an individual. Fuzzy logic is a powerful tool for tackling a wide range of problems in research. It can be used to model complex systems, analyze decision-making processes, and develop systems that can recognize patterns in data. In addition, fuzzy logic can be used to model complex systems such as financial markets and natural phenomena. As fuzzy logic is able to deal with uncertainty and imprecise data, it is particularly well-suited to a wide range of research. Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a method used to determine the best of the options under consideration with respect to the weights and influence of each of the attributes associated with every option. Fuzzy AHP (Analytic Hierarchy Process) is a multi-criteria decision-making method that uses fuzzy set theory to evaluate alternatives. This method seeks to identify the best option from a set of alternatives based on the relative importance of the criteria. The goal of this study is to emphasize a through and in-depth literature evaluation of multi criteria decision making challenges in addition to pinpointing the aspects that contribute most significantly. We have implemented MCDM techniques to propose an effective approach towards decision making of various factors at multiple levels in patients suffering from schizophrenia and observed that the highest ranked Person (P4) with 0.8097 CCi can be inferred to most likely be affected by Schizophrenia, while the person at the bottom of the rank hierarchy (P1) with 0.2813 CCi is least likely to be affected.