Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease
	Nie, Liqiang 1; Zhang, Luming 2; Meng, Lei 3; Song, Xuemeng 4; Chang, Xiaojun 5; Li, Xuelong 6
刊名	ieee transactions on neural networks and learning systems
	2017-07-01
卷号	28 期号:7 页码:1508-1519
关键词	Disease progression modeling future health prediction multisource analysis source consistency temporal regularization
ISSN号	2162-237x
通讯作者	nie, lq (reprint author), shandong univ, sch comp sci & technol, jinan 250100, peoples r china.
产权排序	6
英文摘要	understanding the progression of chronic diseases can empower the sufferers in taking proactive care. to predict the disease status in the future time points, various machine learning approaches have been proposed. however, a few of them jointly consider the dual heterogeneities of chronic disease progression. in particular, the predicting task at each time point has features from multiple sources, and multiple tasks are related to each other in chronological order. to tackle this problem, we propose a novel and unified scheme to coregularize the prior knowledge of source consistency and temporal smoothness. we theoretically prove that our proposed model is a linear model. before training our model, we adopt the matrix factorization approach to address the data missing problem. extensive evaluations on real-world alzheimer's disease data set have demonstrated the effectiveness and efficiency of our model. it is worth mentioning that our model is generally applicable to a rich range of chronic diseases.
学科主题	computer science, artificial intelligence ; computer science, hardware & architecture ; computer science, theory & methods ; engineering, electrical & electronic
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence ; computer science, hardware & architecture ; computer science, theory & methods ; engineering, electrical & electronic
研究领域[WOS]	computer science ; engineering
关键词[WOS]	base-line ; classification ; prediction ; brain
收录类别	SCI
语种	英语
WOS记录号	WOS:000404048300002
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/29086]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Shandong Univ, Sch Comp Sci & Technol, Jinan 250100, Peoples R China 2.Hefei Univ Technol, Dept Elect Engn & Informat Syst, Hefei 230009, Peoples R China 3.Nanyang Technol Univ, Joint NTU Univ British Columbia Res Ctr Excellenc, Singapore 639798, Singapore 4.Natl Univ Singapore, Sch Comp, Singapore 119077, Singapore 5.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Sydney, NSW 2007, Australia 6.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Nie, Liqiang,Zhang, Luming,Meng, Lei,et al. Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease[J]. ieee transactions on neural networks and learning systems,2017,28(7):1508-1519.
APA	Nie, Liqiang,Zhang, Luming,Meng, Lei,Song, Xuemeng,Chang, Xiaojun,&Li, Xuelong.(2017).Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease.ieee transactions on neural networks and learning systems,28(7),1508-1519.
MLA	Nie, Liqiang,et al."Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease".ieee transactions on neural networks and learning systems 28.7(2017):1508-1519.