Abstract
Attention deficit/hyperactivity disorder (ADHD) is one of the most common diseases in school-age children. To date, the diagnosis of ADHD is mainly subjective and studies of objective diagnostic method are of great importance. Although many efforts have been made recently to investigate the use of structural and functional brain images for the diagnosis purpose, few of them are related to ADHD. In this paper, we introduce an automatic classification framework based on brain imaging features of ADHD patients and present in detail the feature extraction, feature selection, and classifier training methods. The effects of using different features are compared against each other. In addition, we integrate multimodal image features using multi-kernel learning (MKL). The performance of our framework has been validated in the ADHD-200 Global Competition, which is a world-wide classification contest on the ADHD-200 datasets. In this competition, our classification framework using features of resting-state functional connectivity (FC) was ranked the 6th out of 21 participants under the competition scoring policy and performed the best in terms of sensitivity and J-statistic.
Highlights
Attention deficit/hyperactivity disorder (ADHD), one of the most commonly diagnosed childhood behavioral disorders, is characterized by inappropriate inattention, impulsivity, and hyperactivity
The 10-fold cross validation (CV) classification results using a single feature are listed in Table 3, in which we compare the CV accuracy using cortical thickness (CT), gray matter probability (GMP), regional homogeneity (ReHo), or ROI-based functional connectivity (FC) as the feature to train the classifier
J-statistic is used by the ADHD-200 Consortium to compare the competition results of participating groups, it is not generally to be recommended (Youden, 1950)
Summary
Attention deficit/hyperactivity disorder (ADHD), one of the most commonly diagnosed childhood behavioral disorders, is characterized by inappropriate inattention, impulsivity, and hyperactivity. ADHD affects at least 5% of school-age children, making them difficult to control their behaviors or focus their attentions. These symptoms may persist into adulthood and result in a lifelong impairment (Biederman et al, 2000). It is very difficult to draw a line between the normal levels of the ADHD symptoms and the clinically significant levels that require interventions. Further studies on objective diagnosis of ADHD are of great significance
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
