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Designing a decision support system for distinguishing adhd from similar children behavioral disorders

机译:设计一个决策支持系统,以区分adhd和相似的儿童行为障碍

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摘要

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.
机译:在这项研究中,设计了决策支持系统,以根据症状和体征将ADHD儿童与其他类似的儿童行为障碍区分开,例如抑郁症,焦虑症,合并症,焦虑和行为障碍。比较了径向基函数和多层神经网络分类的准确性。最后,多层和径向基函数网络的分类网络平均准确率分别达到95.50%和96.62%。我们的结果表明,决策支持系统(尤其是RBF)可能是精神科医生诊断儿童高危行为障碍的良好初步助手。

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