Modeling disease progression via multi-task learning

NeuroImage

Volumn 78, Issue , 2013, Pages 233-248

  Zhou, Jiayu ^a   Liu, Jun ^a   Narayan, Vaibhav A ^b   Ye, Jieping ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

^b JOHNSON AND JOHNSON PHARMACEUTICAL RESEARCH AND DEVELOPMENT   (United States)

Author keywords

ADAS Cog; Alzheimer's disease; Disease progression; Fused Lasso; MMSE; Multi task learning

Indexed keywords

ALGORITHM; ALZHEIMER DISEASE; ALZHEIMER'S DISEASE ASSESSMENT SCALE COGNITIVE SUBSCALE; ARTICLE; BRAIN SIZE; COGNITION; CONTROLLED STUDY; CORTICAL THICKNESS (BRAIN); DISEASE COURSE; DISEASE MARKER; DISEASE MODEL; ENTORHINAL CORTEX; HIPPOCAMPUS; INTERMETHOD COMPARISON; LONGITUDINAL STUDY; MENTAL PERFORMANCE; MENTAL TASK; MILD COGNITIVE IMPAIRMENT; MINI MENTAL STATE EXAMINATION; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTION; PRIORITY JOURNAL; RATING SCALE; SCORING SYSTEM; SINGLE TASK LEARNING ALGORITHM; TEMPORAL CORTEX; WHITE MATTER;

AGED; ALGORITHMS; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; DISEASE PROGRESSION; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; REGRESSION ANALYSIS;

EID: 84877334125     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2013.03.073     Document Type: Article

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