Prediction of individual subject's age across the human lifespan using diffusion tensor imaging: A machine learning approach

NeuroImage

Volumn 75, Issue , 2013, Pages 58-67

  Mwangi, Benson ^a   Hasan, Khader M ^a   Soares, Jair C ^a  

^a UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

Author keywords

Cerebral ageing; Cerebral maturation; Diffusion tensor imaging; Machine learning; Multivariate; Neuroimaging; Relevance vector regression

Indexed keywords

ACCURACY; ADULT; AGE; AGED; AGING; ARTICLE; AXIAL DIFFUSIVITY; BRAIN MATURATION; CEREBRAL PEDUNCLE; CHILD; CINGULUM BUNDLE; CONTROLLED STUDY; CORPUS CALLOSUM; CORRELATION COEFFICIENT; DIFFUSION TENSOR IMAGING; FEMALE; FRACTIONAL ANISOTROPY; HUMAN; LIFESPAN; MACHINE LEARNING; MALE; MEAN DIFFUSIVITY; NEUROIMAGING; NONLINEAR SYSTEM; NORMAL HUMAN; POSTERIOR LONGITUDINAL FASCICULUS; PREDICTION; PRESCHOOL CHILD; PRIORITY JOURNAL; RADIAL DIFFUSIVITY; RADIOLOGICAL PARAMETERS; RELEVANCE VECTOR REGRESSION; WHITE MATTER;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; AGING; ARTIFICIAL INTELLIGENCE; BRAIN; CHILD; CHILD, PRESCHOOL; DIFFUSION TENSOR IMAGING; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFANT; INFANT, NEWBORN; MALE; MIDDLE AGED; YOUNG ADULT;

EID: 84875660261     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2013.02.055     Document Type: Article

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