Basic and Clinical Neuroscience Journal
مجله علوم اعصاب پایه و بالینی
BCN
Medical Sciences
http://bcn.iums.ac.ir
137
journal137
2008-126X
2228-7442
10.32598/bcn
en
jalali
1399
2
1
gregorian
2020
5
1
11
3
online
1
fulltext
en
Discrimination of ADHD Subtypes Using Decision Tree on Behavioral, Neuropsychological, and Neural Markers
Cellular and molecular Neuroscience
Cellular and molecular Neuroscience
Original
Original
<h1><strong>Introduction</strong>: Attention-Deficit/Hyperactivity Disorder (ADHD) is a well-known neurodevelopmental disorder. Diagnosis and treatment of ADHD can often lead to a developmental trajectory toward positive results. The present study aimed at implementing the decision tree method to recognize children with and without ADHD, as well as ADHD subtypes. <br>
<strong>Methods</strong>: In the present study, the subjects included 61 children with ADHD (subdivided into ADHD-I (n=25), ADHD-H (n=14), and ADHD-C (n=22) groups) and 43 typically developing controls matched by IQ and age. The Child Behavior Checklist (CBCL), Integrated Visual And Auditory (IVA) test, and quantitative EEG during eyes-closed resting-state were utilized to evaluate the level of behavioral, neuropsychology, and electrophysiology markers using a decision tree algorithm, respectively.<br>
<strong>Results</strong>: Based on the results, excellent classification accuracy (100%) was obtained to discriminate children with ADHD from the control group. Also, the ADHD subtypes, including combined, inattention, and hyperactive/impulsive subtypes were recognized from others with an accuracy of 80.41%, 84.17%, and 71.46%, respectively. <br>
<strong>Conclusion</strong>: Our results showed that children with ADHD can be recognized from the healthy controls based on the neuropsychological data (sensory-motor parameters of IVA). Also, subtypes of ADHD can be distinguished from each other using behavioral, neuropsychiatric and electrophysiological parameters. The findings suggested that the decision tree method may present an efficient and accurate diagnostic tool for the clinicians.</h1>
ADHD subtypes, Behavior, Neuropsychology, Electrophysiology, Decision tree
359
368
http://bcn.iums.ac.ir/browse.php?a_code=A-10-1871-1&slc_lang=en&sid=1
Mohammad
Rostami
psy.rostami@gmail.com
13700319475328460027400
13700319475328460027400
No
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.
Sajjad
Farashi
sajjad_farashi@yahoo.com
13700319475328460027401
13700319475328460027401
No
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.
Reza
Khosrowabadi
r_khosroabadi@sbu.ac.ir
13700319475328460027402
13700319475328460027402
Yes
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.
Hamidreza
Pouretemad
r_khosroabadi@sbu.ac.ir
13700319475328460027403
13700319475328460027403
No
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.