How early can we predict Alzheimer's disease using computational anatomy?

Neurobiology of Aging

Volumn 34, Issue 12, 2013, Pages 2815-2826

  Adaszewski, Stanisław ^a,b   Dukart, Juergen ^a   Kherif, Ferath ^a   Frackowiak, Richard ^a   Draganski, Bogdan ^a,c  

^a LAUSANNE UNIVERSITY HOSPITAL   (Switzerland)

^b WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

^c MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

Author keywords

Alzheimer's disease; Biomarker; Mild cognitive impairment; Structural magnetic resonance imaging

Indexed keywords

AGED; ALZHEIMER DISEASE; AMYGDALOID NUCLEUS; ANGULAR GYRUS; ARTICLE; BRAIN REGION; BRAIN SIZE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PREDICTION; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DISEASE MARKER; FEMALE; HIPPOCAMPUS; HUMAN; INFORMATION PROCESSING; INFORMATION RETRIEVAL; INSULA; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; PARAHIPPOCAMPAL GYRUS; PARIETAL LOBE; PREDICTIVE VALUE; PRIORITY JOURNAL; PUTAMEN; SUPPORT VECTOR MACHINE; SUPRAMARGINAL GYRUS; THALAMUS; VOXEL BASED MORPHOMETRY;

ALZHEIMER'S DISEASE; BIOMARKER; MILD COGNITIVE IMPAIRMENT; STRUCTURAL MAGNETIC RESONANCE IMAGING;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; ANATOMY; ARTIFICIAL INTELLIGENCE; ATROPHY; BRAIN; EARLY DIAGNOSIS; FEMALE; FORECASTING; HIPPOCAMPUS; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MILD COGNITIVE IMPAIRMENT; PARIETAL LOBE; TEMPORAL LOBE; TIME FACTORS;

EID: 84884125608     PISSN: 01974580     EISSN: 15581497     Source Type: Journal    
DOI: 10.1016/j.neurobiolaging.2013.06.015     Document Type: Article

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