title: Designing a decision support system for distinguishing ADHD from similar children behavioral disorders.
abstract: 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.
authors.affiliation: Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.
authors.forename: Mona
authors.initials: M
authors.lastname: Delavarian
authors.forename: Farzad
authors.initials: F
authors.lastname: Towhidkhah
authors.forename: Parvin
authors.initials: P
authors.lastname: Dibajnia
authors.forename: Shahriar
authors.initials: S
authors.lastname: Gharibzadeh
mesh_terms: D001289:Attention Deficit Disorder with Hyperactivity / Q000175:diagnosis*; D002675:Child, Preschool; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D003937:Diagnosis, Differential; D003951:Diagnostic Errors / Q000517:prevention & control; D006801:Humans; D001523:Mental Disorders / Q000175:diagnosis*