Attention Deficit Hyperactivity Disorder: Behavioral or Neuro-developmental Disorder Testing the HiTOP Framework Using Machine Learning Methods

Background: In current study, we aimed to investigate if Attention Deficit Hyperactivity Disorder (ADHD) is better to be categorized among behavioral or neurodevelopmental disorders, based on some familial and environmental factors. 
Methods: We conducted correlation analysis to identify psychiatric disorders in the dataset which have an important impact on ADHD. Also, we used machine learning-based approaches combined with a feature selection algorithm to cluster and classify ADHD as a behavioral or neurodevelopmental disorder.
Results: Model evaluation showed that ADHD is clustered in the group of behavioral disorders with the accuracy of 78%. Furthermore, Support Vector Machine (SVM) classified ADHD as a behavioral disorder with the accuracy of 72.66% and as a neurodevelopmental disorder with the accuracy of 60.07%.
Conclusion: In sum, we can say that our findings support categorizations systems like HiTOP in comparison to DSM-5. However, as biological factors were not included in our analysis, it should be considered with caution and examined in future researches.