Skip to Main Content
An attempt has been made to develop a fuzzy-logic (FL)-based screening and prediction tool for adult psychoses, a group of look-alike mental illnesses showing varying cause-effect relations among the patients. Gathering information of psychiatric patients is a big hurdle for some ethical reasons. Moreover, due to the gross individualization of the medical logic, doctors' opinions regarding the preliminary identification of the psychotic diseases vary at large. The basic philosophy of this research is to render a low-cost good approximation for the screening of seven adult psychoses and eventually to determine the most predominant one using FL-based expert systems. It shows how the complex decision-making process of adult psychoses can be modeled using the concept of FL. This paper differs from others' works in the following ways: (1) utilized data have more similarity with the real-life data, as those are collected from some practicing psychiatrists; (2) successful implementation of a unique method of screening the psychiatric patients; and (3) efficient identification of important factor(s) for each response.