Subspace Regularized Sparse Multitask Learning for Multiclass Neurodegenerative Disease Identification

IEEE Transactions on Biomedical Engineering

Volumn 63, Issue 3, 2016, Pages 607-618

  Zhu, Xiaofeng ^a   Suk, Heung Il ^b   Lee, Seong Whan ^b   Shen, Dinggang ^a,b  

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

^b Korea University   (South Korea)

Author keywords

Alzheimer's disease; feature selection; mild cognitive impairment; multi class classification; neuroimaging data analysis; sparse coding; subspace learning

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIAGNOSIS; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; LEARNING SYSTEMS; NEURODEGENERATIVE DISEASES; NEUROIMAGING;

ALZHEIMER'S DISEASE; MILD COGNITIVE IMPAIRMENTS; MULTI-CLASS CLASSIFICATION; SPARSE CODING; SUBSPACE LEARNING;

COMPUTER AIDED DIAGNOSIS;

AGED; ALZHEIMER DISEASE; ANTERIOR COMMISSURE; ARTICLE; CLINICAL DEMENTIA RATING; DAILY LIFE ACTIVITY; DIGITAL IMAGING AND COMMUNICATIONS IN MEDICINE; DISCRIMINANT ANALYSIS; DISEASE CLASSIFICATION; FEMALE; HUMAN; LEARNING ALGORITHM; LOCALITY PRESERVING PROJECTION; MAJOR CLINICAL STUDY; MALE; MINI MENTAL STATE EXAMINATION; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; POSITRON EMISSION TOMOGRAPHY; PROCEDURES; VERY ELDERLY;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; BRAIN; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; NEUROIMAGING; POSITRON-EMISSION TOMOGRAPHY;

EID: 84962091523     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2015.2466616     Document Type: Article

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