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Classification of the most Significant Psychological Symptoms in Mental Patients with Depression using Bayesian Network

The classification of mental illness is a key aspect of psychiatry and other mental health professions and an important issue for people who may be diagnosed. In this paper, a data set of 91 records of patients with depression has been used. The main objective of this study was to find an optimum model of psychological factors that lead these patients to have thoughts of death or suicide, in order to achieve the sooner the possible the appropriate treatment. For this reason, fuzzy logic was used in the entire set of factors (Model 1), in order to classify the most significant ones. Next step was to use, the resulted factors in three more models consisted of six (Model 2 and 3) and five factors (Model 4). Bayesian networks have been utilized in these models and the most suitable model has emerged. The results of these experiments, are in accordance with the expert's opinion that the most significant factors that affects the mental patients with depression to have thoughts of death or suicide are mood depression, losing of interest or pleasure, unworthingness/guilt, living in a city and concentration in thoughts.