Benefits of fuzzy logic in the assessment of intellectual disability

Among the artificial intelligence techniques that successfully support computer assisted decision making, fuzzy logic has proved to be a powerful tool in various fields. In particular it is appreciated by clinical practitioners because of their approaches to take a decision require to deal with uncertainties and vagueness in the knowledge and information. One field in which fuzzy sets theory can be applied with great benefit is psychopathology due to the high prominence of sources of uncertainty, that should be taken into account when the diagnosis of intellectual disability must be formulated. Therefore clinical psychologists have often to deal with comorbidities that make the decision process harder because they must evaluate different assessment tools for a correct diagnosis. In our work we investigate the application of computational intelligence methods, and in particular of approaches based on fuzzy logic and its hybridizations, in the psychological assessment by means of theoretical studies and practical experiments with data collected from patients affected by different levels of intellectual disability. In this paper we present a detailed review of the experimental application, with patients under treatment in a clinical centre, of methodologies we propose to generate fuzzy expert systems for the assessment of intellectual disability. Specifically we highlight, with numerical results, how they can be beneficial for the diagnosis and improve efficacy of the administration of psycho-diagnostic instruments and the efficiency of the assessment.