Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

Frontiers in Systems Neuroscience

Volumn , Issue JULY 2012, 2012, Pages

  Eloyan, Ani ^a   Muschelli, John ^a,b   Nebel, Mary Beth ^b   Liu, Han ^a,c   Han, Fang ^a   Zhao, Tuo ^c   Barber, Anita ^b   Joel, Suresh ^b   Pekar, James J ^b   Mostofsky, Stewart ^b   Caffo, Brian ^a  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c Johns Hopkins University   (United States)

Author keywords

Gradient boosting; Random forest; Singular value decomposition; Voxelbased morphometry

Indexed keywords

ADOLESCENT; ADULT; AGE DISTRIBUTION; ALGORITHM; ARTICLE; ATTENTION DEFICIT DISORDER; AUTOMATION; BRAIN REGION; CHILD; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; DISEASE MARKER; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HANDEDNESS; HUMAN; INTELLIGENCE QUOTIENT; MALE; MOTOR CORTEX; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTION; RANDOM FOREST; SCHOOL CHILD; SENSITIVITY AND SPECIFICITY;

EID: 84864968008     PISSN: 16625137     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnsys.2012.00061     Document Type: Article

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