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High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer Disease Progression Prediction
Published on Jan 16, 20133928 Views
Alzheimer disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Regression analysis has been studied to relate neuroimaging m
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Chapter list
High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction00:00
Outline00:31
Backgrounds and Motivations00:44
Major Diseases Are Important Concerns in Modern Society (1)00:47
Major Diseases Are Important Concerns in Modern Society (2)00:56
Longitudinal Multi-Task Regression of Cognitive Trajectories of MRI Measures (1)01:07
Longitudinal Multi-Task Regression of Cognitive Trajectories of MRI Measures (2)02:19
Longitudinal Multi-Task Regression of Cognitive Trajectories of MRI Measures (3)03:23
Challenges and Opportunities in Designing Longitudinal Multi-Task Regression Models (1)03:58
Challenges and Opportunities in Designing Longitudinal Multi-Task Regression Models (2)04:17
High-Order Multi-Task Feature Learning05:47
Association of Longitudinal Imaging Markers and AD Progression (1)05:56
Association of Longitudinal Imaging Markers and AD Progression (2)06:37
Association of Longitudinal Imaging Markers and AD Progression (3)07:04
Longitudinal Multi-Task Feature Learning (1)07:59
Longitudinal Multi-Task Feature Learning (2)08:33
Longitudinal Multi-Task Feature Learning (3)08:48
High-Order Multi-Task Correlations09:07
High-Order Multi-Task Feature Learning11:24
An Ecient Solution Algorithm with Guaranteed Convergence12:00
Experimental Results12:43
The Alzheimer's Disease Neuroimaging Initiative (ADNI)12:51
Improved Cognitive Score Progression Prediction from Longitudinal Imaging Markers13:32
Identi cation of Longitudinal Imaging Markers14:13
Questions & Answers15:06