Disease state prediction from resting state functional connectivity

Magnetic Resonance in Medicine

Volumn 62, Issue 6, 2009, Pages 1619-1628

  Craddock, R Cameron ^a,b   Holtzheimer III, Paul E ^b   Hu, Xiaoping P ^c,d   Mayberg, Helen S ^b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c Emory University   (United States)

^d NONE   (United States)

Author keywords

Biomarker; Disease state prediction; Feature selection; Functional connectivity; Major depressive disorder (MDD); Multivariate pattern analysis (MVPA); Support vector classification (SVC)

Indexed keywords

BIOMARKERS; FORECASTING; FUNCTIONAL NEUROIMAGING; MULTIVARIANT ANALYSIS; RELIABILITY; VECTORS;

DISEASE STATE; FUNCTIONAL CONNECTIVITY; MAJOR DEPRESSIVE DISORDER (MDD); MULTIVARIATE PATTERN ANALYSIS; SUPPORT VECTOR CLASSIFICATION;

FEATURE EXTRACTION;

ADULT; ALGORITHM; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DISEASE COURSE; FILTER; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; INTERMETHOD COMPARISON; MAJOR DEPRESSION; MENTAL HEALTH; NEUROIMAGING; NOISE; PREDICTION; PSYCHIATRIC DIAGNOSIS; RELIABILITY; SUPPORT VECTOR MACHINE;

EID: 73149109077     PISSN: 07403194     EISSN: 15222594     Source Type: Journal    
DOI: 10.1002/mrm.22159     Document Type: Article

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