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1.
Comput Methods Programs Biomed ; 190: 105354, 2020 Jul.
Article in English | MEDLINE | ID: mdl-32035305

ABSTRACT

BACKGROUND: Mental disorders, according to the definition of World Health Organization, consist of a wide range of signs, which are generally specified by a combination of unusual thoughts, feelings, behavior, and relationships with others. Social anxiety disorder (SAD) is one of the most prevalent mental disorders, described as permanent and severe fear or feeling of embarrassment in social situations. Considering the imprecise nature of SAD symptoms, the main objective of this study was to generate an intelligent decision support system for SAD diagnosis, using Adaptive neuro-fuzzy inference system (ANFIS) technique and to conduct an evaluation method, using sensitivity, specificity and accuracy metrics. METHOD: In this study, a real-world dataset with the sample size of 214 was selected and used to generate the model. The method comprised a multi-stage procedure named preprocessing, classification, and evaluation. The preprocessing stage, itself, consists of three steps called normalization, feature selection, and anomaly detection, using the Self-Organizing Map (SOM) clustering method. The ANFIS technique with 5-fold cross-validation was used for the classification of social anxiety disorder. RESULTS AND CONCLUSION: The preprocessed dataset with seven input features were used to train the ANFIS model. The hybrid optimization learning algorithm and 41 epochs were used as optimal learning parameters. The accuracy, sensitivity, and specificity metrics were reported 98.67%, 97.14%, and 100%, respectively. The results revealed that the proposed model was quite appropriate for SAD diagnosis and in line with findings of other studies. Further research study addressing the design of a decision support system for diagnosing the severity of SAD is recommended.


Subject(s)
Decision Support Systems, Clinical , Diagnosis, Computer-Assisted , Phobia, Social/diagnosis , Algorithms , Artificial Intelligence , Fuzzy Logic , Humans
2.
Int J Soc Psychiatry ; 51(1): 13-22, 2005 Mar.
Article in English | MEDLINE | ID: mdl-15864971

ABSTRACT

BACKGROUND: The study of distorted beliefs about responsibility attitude and interpretation has become the central theme in Salkovskis' (1985) and Rachman and Hodgson's (1980) models of Obsessive-Compulsive Disorder (OCD). AIMS: The aim of this research is to assess the responsibility attitude in Iranian OCD patients. METHODS: Twenty OCD patients were selected through available sampling from the case referred to psychology clinics. Two other patient groups comprised of 20 non-OCD anxiety disorder patients and 20 non-clinical participants were also chosen as comparison groups. All participants completed the Responsibility Attitude Scale (RAS) and Responsibility Interpretation Questionnaire (RIQ). RESULTS: Analyses revealed statistically significant differences between OCD group and comparison groups on both RAS and RIQ. In addition, both RAS and RIQ scores were associated with the severity of OCD assessed by the Yale-Brown scale. CONCLUSIONS: These findings suggest that responsibility attitude and interpretations are the prominent features of OCD in Iranian patients and are associated with the severity of illness.


Subject(s)
Culture , Ethnicity/psychology , Obsessive-Compulsive Disorder/psychology , Perceptual Distortion , Social Responsibility , Adult , Anxiety Disorders/diagnosis , Anxiety Disorders/psychology , Cognitive Behavioral Therapy , Female , Humans , Iran , Male , Obsessive-Compulsive Disorder/diagnosis , Personality Inventory/statistics & numerical data , Psychometrics/statistics & numerical data , Reference Values , Referral and Consultation , Self Concept , Surveys and Questionnaires
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