Differentiation between resting-state fMRI data from ADHD and normal subjects: Based on functional connectivity and machine learning

研究成果: Paper

10 引文 斯高帕斯(Scopus)

摘要

Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder which is quite common in childhood, with an estimated prevalence of 5-8%, and often persists into adolescence and adulthood. It is further characterized as inappropriate developmentally symptoms of inattention, impulsiveness, motor over-activity and restlessness. The aim of this study is to evaluate the feasibility of diagnosing ADHD by analyzing the resting-state functional magnetic resonance imaging (fMRI) data. In addition to confirming the previously observed three areas including anterior cingulate cortex (ACC), posterior cingulated cortex (PCC) and ventro medial prefrontal cortex (vmPFC), we also found significant differences in cerebellum, motor cortex and temporal lobe between ADHD and normal humans based on regional homogeneity analysis of the dataset from 73 children with ADHD and 76 normal children. Extracting features from these seven brain areas and utilizing the LDA classifier, the average accuracy of distinguishing normal and ADHD children reaches 80.08% though 50 times of 2-fold validation. Experimental results demonstrate the feasibility of ADHD diagnosis based on the combination of functional connectivity of resting-state fMRI and machine learning technique.

原文English
頁面294-298
頁數5
DOIs
出版狀態Published - 2012 十二月 1
事件2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012 - Taichung, Taiwan
持續時間: 2012 十一月 162012 十一月 18

Other

Other2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012
國家Taiwan
城市Taichung
期間12-11-1612-11-18

All Science Journal Classification (ASJC) codes

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    Liang, S-F., Hsieh, T. H., Chen, P. T., Wu, M-L., Kung, C-C., Lin, C-Y., & Shaw, F-Z. (2012). Differentiation between resting-state fMRI data from ADHD and normal subjects: Based on functional connectivity and machine learning. 294-298. 論文發表於 2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012, Taichung, Taiwan. https://doi.org/10.1109/iFUZZY.2012.6409719