Accurate prediction of AD patients using cortical thickness networks

doi:10.1007/s00138-012-0462-0

	Accurate prediction of AD patients using cortical thickness networks
	Dai, Dai 1; He, Huiguang1 ; Vogelstein, Joshua T.2; Hou, Zengguang1
发表期刊	MACHINE VISION AND APPLICATIONS
	2013-10-01
卷号	24 期号:7 页码:1445-1457
文章类型	Article
摘要	It is widely believed that human brain is a complicated network and many neurological disorders such as Alzheimer's disease (AD) are related to abnormal changes of the brain network architecture. In this work, we present a kernel-based method to establish a network for each subject using mean cortical thickness, which we refer to hereafter as the individual's network. We construct individual networks for 83 subjects, including AD patients and normal controls (NC), which are taken from the Open Access Series of Imaging Studies database. The network edge features are used to make prediction of AD/NC through the sophisticated machine learning technology. As the number of edge features is much more than that of samples, feature selection is applied to avoid the adverse impact of high-dimensional data on the performance of classifier. We use a hybrid feature selection that combines filter and wrapper methods, and compare the performance of six different combinations of them. Finally, support vector machines are trained using the selected features. To obtain an unbiased evaluation of our method, we use a nested cross validation framework to choose the optimal hyper-parameters of classifier and evaluate the generalization of the method. We report the best accuracy of 90.4 % using the proposed method in the leave-one-out analysis, outperforming that using the raw cortical thickness data by more than 10 %.
关键词	Classification Alzheimer's Disease Network Cortical Thickness
WOS标题词	Science & Technology ; Technology
DOI	10.1007/s00138-012-0462-0
关键词[WOS]	MILD COGNITIVE IMPAIRMENT ; DIMENSIONAL PATTERN-CLASSIFICATION ; ALZHEIMERS-DISEASE ; BRAIN ATROPHY ; MCI PATIENTS ; MRI ; MORPHOMETRY ; VALIDATION ; CONVERSION ; DIAGNOSIS
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61271151 ; Sci. & Tech. Aiding the Disabled Program of the Chinese Academy of Sciences(KGCX2-YW-618) ; 61228103 ; 61175076)
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Cybernetics ; Engineering, Electrical & Electronic
WOS记录号	WOS:000324499000011
引用统计	被引频次：39[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3505
专题	复杂系统认知与决策实验室_先进机器人
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Johns Hopkins Univ, Baltimore, MD USA
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Dai, Dai,He, Huiguang,Vogelstein, Joshua T.,et al. Accurate prediction of AD patients using cortical thickness networks[J]. MACHINE VISION AND APPLICATIONS,2013,24(7):1445-1457.
APA	Dai, Dai,He, Huiguang,Vogelstein, Joshua T.,&Hou, Zengguang.(2013).Accurate prediction of AD patients using cortical thickness networks.MACHINE VISION AND APPLICATIONS,24(7),1445-1457.
MLA	Dai, Dai,et al."Accurate prediction of AD patients using cortical thickness networks".MACHINE VISION AND APPLICATIONS 24.7(2013):1445-1457.