A Weighted Discriminative Dictionary Learning Method for Depression Disorder Classification using fMRI Data

doi:10.1109/BDCloud-SocialCom-SustainCom.2016.97

CORC > 自动化研究所 > 中国科学院自动化研究所 > 精密感知与控制研究中心 > 人工智能与机器学习

	A Weighted Discriminative Dictionary Learning Method for Depression Disorder Classification using fMRI Data
	Wang Xin1 ; Ren Yanshuang 2; Yang Yehui1 ; Zhang Wensheng1 ; Neal N. Xiong 3
	2016
会议日期	2016-10-8
会议地点	Atlanta, GA, USA
DOI	10.1109/BDCloud-SocialCom-SustainCom.2016.97
英文摘要	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.
内容类型	会议论文
源URL	[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]. 见:. Atlanta, GA, USA. 2016-10-8.