A Weighted Discriminative Dictionary Learning Method for Depression Disorder Classification using fMRI Data
Wang Xin1; Ren Yanshuang2; Yang Yehui1; Zhang Wensheng1; Neal N. Xiong3
2016
会议名称2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom)
会议日期2016-10-8
会议地点Atlanta, GA, USA
摘要In this paper, we present a novel depression disorder classification algorithm, named weighted discriminative dictionary learning (WDDL), based on functional magnetic
resonance imaging (fMRI) data. The underlying relationship between samples and dictionary atoms is exploited by introducing an adaptive weighting scheme. Tested on fMRI data of 29 patients with depression and 29 healthy controls, our algorithm outperforms all other classification methods compared in this work. Furthermore, we detect the discriminative brain regions of patients which can reveal the pathogenesis of depression
disorder.

DOI10.1109/BDCloud-SocialCom-SustainCom.2016.97
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文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/14845
专题精密感知与控制研究中心_人工智能与机器学习
通讯作者Zhang Wensheng
作者单位1.Institute of Automation, Chinese Academy of Sciences
2.Department of Radiology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences
3.Department of Business and Computer Science, Southwestern Oklahoma State University
推荐引用方式
GB/T 7714
Wang Xin,Ren Yanshuang,Yang Yehui,et al. A Weighted Discriminative Dictionary Learning Method for Depression Disorder Classification using fMRI Data[C],2016.
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