Computational Decision Support System for ADHD Identification
文献类型：期刊论文
| 作者 | Senuri De Silva3 |
| 刊名 | International Journal of Automation and Computing
 |
| 出版日期 | 2021 |
| 卷号 | 18期号:2页码:233-255 |
| 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) |
| ISSN号 | 1476-8186 |
| DOI | 10.1007/s11633-020-1252-1 |
| 英文摘要 | 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. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/44019]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | 1.Department of Communication Disorders and Special Education, Old Dominion University, Norfolk 23529, USA 2.Department of Computer Science, College of Science, Old Dominion University, Norfolk 23529, USA 3.Department of Computer Science and Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka |
| 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. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
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。