ADHD Classification Within and Cross Cohort Using an Ensembled Feature Selection Framework | |
Yao DR(姚东任); Sun HL(孙海伦); Guo XJ(郭晓杰); Vince D. Calhoun; Sun L(孙黎); Sui J(隋婧) | |
2019 | |
会议名称 | 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI) |
会议日期 | 2019/04/01 |
会议地点 | 意大利 |
摘要 |
Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder that often persists into adulthood. However, as lacking objective measures, several studies have questioned the stability in diagnosing of ADHD from childhood to adulthood. In this study, we propose a novel feature selection framework based on functional connectivity (FCs) pattern, the so-called `FS_RIWEL,' which could classify ADHD from agematched healthy controls (HCs) with ~80% accuracy (both for children and adults). More importantly, the feature space learned from child ADHD dataset can discriminate adult ADHD from HCs at ~70% accuracy. To the best of our knowledge, this is the first attempt to perform a cross-cohort prediction between the adult and child ADHD using FC features. In addition, the most frequently selected FCs indicate that ADHD exhibit widely-impaired FC patterns in frontoparietal, basal ganglia, cerebellum network and so on suggesting that FCs may serve as potential biomarkers for ADHD diagnosis. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 医学影像处理与分析 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44782 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Sui J(隋婧) |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University 4.The Mind Research Network, and Department of Electrical and Computer Engineering, University of New Mexico |
推荐引用方式 GB/T 7714 | Yao DR,Sun HL,Guo XJ,et al. ADHD Classification Within and Cross Cohort Using an Ensembled Feature Selection Framework[C],2019. |
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ADHD classification (243KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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