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ABSTRACT
Machine learning tools aid many Alzheimer's disease-related investigations by enabling multisource data fusion and biomarker identification as well as analysis of functional brain connectivity.
INDEX TERMS
sensor fusion, brain, diseases, learning (artificial intelligence), medical image processing, functional brain connectivity, machine learning approach, neuroimaging study, Alzheimer disease, multisource data fusion, biomarker identification, Magnetic resonance imaging, Positron emission tomography, Machine learning, Neuroimaging, Genetics, Alzheimer's disease, Multiple kernel learning, Machine learning techniques, Neuroimaging, Alzheimer's disease
CITATION
"Machine Learning Approaches for the Neuroimaging Study of Alzheimer's Disease", Computer, vol. 44, no. , pp. 99-101, April 2011, doi:10.1109/MC.2011.117
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