Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 940-947

  Wan, Jing ^a,b   Zhang, Zhilin ^c   Yan, Jingwen ^a   Li, Taiyong ^a,d   Rao, Bhaskar D ^c   Fang, Shiaofen ^b   Kim, Sungeun ^a   Risacher, Shannon L ^a   Saykin, Andrew J ^a   Shen, Li ^a,b  

^a INDIANA UNIVERSITY   (United States)

^b PURDUE UNIVERSITY   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d SOUTHWESTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALZHEIMER'S DISEASE; COGNITIVE FUNCTIONS; COGNITIVE PERFORMANCE; COGNITIVE TESTS; COMPACT SETS; DEPENDENCE RELATION; MRI SCAN; MULTITASK LEARNING; MULTIVARIATE REGRESSION MODELS; PREDICTION PERFORMANCE; PRIOR KNOWLEDGE; REGRESSION METHOD; STRUCTURAL CHANGE;

COMPUTER VISION; FORECASTING; LEARNING ALGORITHMS;

NEUROIMAGING;

EID: 84866683998     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247769     Document Type: Conference Paper

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