Neurodegenerative disease diagnosis using incomplete multi-modality data via matrix shrinkage and completion

NeuroImage

Volumn 91, Issue , 2014, Pages 386-400

  Thung, Kim Han ^a   Wee, Chong Yaw ^a   Yap, Pew Thian ^a   Shen, Dinggang ^a,b  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b Korea University   (South Korea)

Author keywords

Classification; Data imputation; Matrix completion; Multi task learning

Indexed keywords

AMYLOID BETA PROTEIN; TAU PROTEIN;

AGED; ALZHEIMER DISEASE; ARTICLE; CEREBROSPINAL FLUID ANALYSIS; CLASSIFICATION; CLASSIFIER; CONTROLLED STUDY; DATA PROCESSING; DEGENERATIVE DISEASE; FEMALE; HUMAN; INTERMETHOD COMPARISON; LEARNING ALGORITHM; MAJOR CLINICAL STUDY; MALE; MILD COGNITIVE IMPAIRMENT; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; POSITRON EMISSION TOMOGRAPHY; PREDICTION; PRIORITY JOURNAL;

CLASSIFICATION; DATA IMPUTATION; MATRIX COMPLETION; MULTI-TASK LEARNING;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; DATABASES, FACTUAL; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; NEURODEGENERATIVE DISEASES; NEUROIMAGING; NEUROPSYCHOLOGICAL TESTS; POSITRON-EMISSION TOMOGRAPHY; PSYCHIATRIC STATUS RATING SCALES; PSYCHOMOTOR PERFORMANCE; REPRODUCIBILITY OF RESULTS; WECHSLER SCALES;

EID: 84896353646     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.01.033     Document Type: Article

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