Knowledge Commons of Institute of Automation,CAS
Computational Decision Support System for ADHD Identification | |
Senuri De Silva1 | |
发表期刊 | International Journal of Automation and Computing |
ISSN | 1476-8186 |
2021 | |
卷号 | 18期号:2页码:233-255 |
摘要 | Attention deficit/hyperactivity disorder (ADHD) is a common disorder among children. ADHD often prevails into adulthood, unless proper treatments are facilitated to engage self-regulatory systems. Thus, there is a need for effective and reliable mechanisms for the early identification of ADHD. This paper presents a decision support system for the ADHD identification process. The proposed system uses both functional magnetic resonance imaging (fMRI) data and eye movement data. The classification processes contain enhanced pipelines, and consist of pre-processing, feature extraction, and feature selection mechanisms. fMRI data are processed by extracting seed-based correlation features in default mode network (DMN) and eye movement data using aggregated features of fixations and saccades. For the classification using eye movement data, an ensemble model is obtained with 81% overall accuracy. For the fMRI classification, a convolutional neural network (CNN) is used with 82% accuracy for the ADHD identification. Both ensemble models are proved for overfitting avoidance. |
关键词 | Attention deficit/hyperactivity disorder (ADHD) functional magnetic resonance imaging (fMRI) eye movement data seed-based correlation ensembled model convolutional neural network (CNN) default mode network (DMN) saccades fixations ADHD-Care decision support system (DDS) |
DOI | 10.1007/s11633-020-1252-1 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44019 |
专题 | 学术期刊_Machine Intelligence Research |
作者单位 | 1.Department of Computer Science and Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka 2.Department of Computer Science, College of Science, Old Dominion University, Norfolk 23529, USA 3.Department of Communication Disorders and Special Education, Old Dominion University, Norfolk 23529, USA |
推荐引用方式 GB/T 7714 | Senuri De Silva. Computational Decision Support System for ADHD Identification[J]. International Journal of Automation and Computing,2021,18(2):233-255. |
APA | Senuri De Silva.(2021).Computational Decision Support System for ADHD Identification.International Journal of Automation and Computing,18(2),233-255. |
MLA | Senuri De Silva."Computational Decision Support System for ADHD Identification".International Journal of Automation and Computing 18.2(2021):233-255. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
IJAC-2020-05-112.pdf(1937KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
个性服务 |
推荐该条目 |
保存到收藏夹 |
查看访问统计 |
导出为Endnote文件 |
谷歌学术 |
谷歌学术中相似的文章 |
[Senuri De Silva]的文章 |
百度学术 |
百度学术中相似的文章 |
[Senuri De Silva]的文章 |
必应学术 |
必应学术中相似的文章 |
[Senuri De Silva]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论