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Designing a Decision Support System for Distinguishing ADHD from Similar Children Behavioral Disorders

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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.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

    Mona Delavarian, Farzad Towhidkhah & Shahriar Gharibzadeh

  2. Department of Psychiatry, Shahid Beheshti Medical University, Tehran, Iran

    Parvin Dibajnia

  3. Neuromuscular Systems Laboratory, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

    Shahriar Gharibzadeh

Authors
  1. Mona Delavarian
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  2. Farzad Towhidkhah
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  3. Parvin Dibajnia
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  4. Shahriar Gharibzadeh
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Correspondence to Shahriar Gharibzadeh.

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Delavarian, M., Towhidkhah, F., Dibajnia, P. et al. Designing a Decision Support System for Distinguishing ADHD from Similar Children Behavioral Disorders. J Med Syst 36, 1335–1343 (2012). https://doi.org/10.1007/s10916-010-9594-9

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  • DOI: https://doi.org/10.1007/s10916-010-9594-9

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