Random forest-based similarity measures for multi-modal classification of Alzheimer's disease

Neurodegenerative disorders, such as Alzheimer's disease, are associated with changes in multiple neuroimaging and biological measures. These may provide complementary information for diagnosis and prognosis. We present a multi-modality classification framework in which manifolds are constructe...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 65; pp. 167 - 175
Main Authors:	Gray, Katherine R., Aljabar, Paul, Heckemann, Rolf A., Hammers, Alexander, Rueckert, Daniel
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier Inc 15-01-2013 Elsevier Elsevier Limited
Subjects:	Accuracy Adult and adolescent clinical studies Aged Alzheimer Disease - classification Alzheimer Disease - diagnosis Alzheimer Disease - physiopathology Alzheimer's disease Artificial Intelligence Biological and medical sciences Biomarkers Biomarkers - analysis Cerebrospinal fluid biomarkers Classification Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases Female Genetics Glucose Humans Magnetic Resonance Imaging Male Medical imaging Medical sciences Metabolism Methods Mild cognitive impairment Models, Theoretical Multi-modality classification Neurology NMR Nuclear magnetic resonance Organic mental disorders. Neuropsychology Positron emission tomography Psychology. Psychoanalysis. Psychiatry Psychopathology. Psychiatry Studies Magnetic resonance imaging Mild cognitive impairment Multi-modality classification Genetics Cerebrospinal fluid biomarkers Alzheimer's disease Positron emission tomography Nervous system diseases Alzheimer disease Biological marker Cerebrospinal fluid Nuclear magnetic resonance imaging Cerebral disorder Central nervous system disease Degenerative disease mild cognitive impairment Emission tomography
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