J Med Syst - Designing a decision support system for distinguishing ADHD from similar children behavioral disorders.

Tópicos

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Resumo

In this study, a decision support system was designed to distinguish children with ADHD from other similar children behavioral disorders such as depression, anxiety, comorbid depression and anxiety and conduct disorder based on the signs and symptoms. Accuracy of classifying with Radial basis function and multilayer neural networks were compared. Finally, the average accuracy of the networks in classification reached to 95.50% and 96.62% by multilayer and radial basis function networks respectively. Our results indicate that a decision support system, especially RBF, may be a good preliminary assistant for psychiatrists in diagnosing high risk behavioral disorders of children.

Resumo Limpo

studi decis support system design distinguish children adhd similar children behavior disord depress anxieti comorbid depress anxieti conduct disord base sign symptom accuraci classifi radial basi function multilay neural network compar final averag accuraci network classif reach multilay radial basi function network respect result indic decis support system especi rbf may good preliminari assist psychiatrist diagnos high risk behavior disord children

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