Article Title: Designing a Fuzzy Expert Decision Support System Based on Decreased Rules to Specify Depression
DOI: https://doi.org/10.1007/978-981-10-86.
Chapter: 15 Pages: 197-213
Authors: Hamed Movaghari, Rouhollah Maghsoudi, Abolfazl Mohammadi
Editors: Shahram Montaser Kouhsari, Ali Safaei
Abstract: Depression is a psychological disorder, if it doesn’t be diagnosed and cured in time, can effect on quality of humans’ life in wide dimensions. Thus, diagnosis easily and quickly is necessary need of sociality’s generally healthy. The aim of this paper is designing an fuzzy decision support system to implement BDI-II. Questions for BDI-II are grouped into multiple factors. In medical sciences, disorders, and diseases that lack high confidence and complexity in diagnosis, intelligent systems have better confidence capacity in diagnosis. In this investment, the structure is designed in form of two factors and five factors. The results show that designed system with two factors compared to five factors structure with 94.2% diagnostic power has implementations train data of BDI-II. Hence, in future, the psychologist can use this system as a decision support system of decision support in clinical and hospital diagnoses.
Keywords: Fuzzy logic, ANFIS, Depression, BDI-II
Designing a Fuzzy Expert Decision Support System Based on Decreased Rules to Specify Depression