Topological graph kernel on multiple thresholded functional connectivity networks for mild cognitive impairment classification

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چکیده

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Topological graph kernel on multiple thresholded functional connectivity networks for mild cognitive impairment classification.

Recently, brain connectivity networks have been used for classification of Alzheimer's disease and mild cognitive impairment (MCI) from normal controls (NC). In typical connectivity-networks-based classification approaches, local measures of connectivity networks are first extracted from each region-of-interest as network features, which are then concatenated into a vector for subsequent featur...

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Background: Early diagnosis of patients in the early stages of Alzheimer's, known as mild cognitive impairment, is of great importance in the treatment of this disease. If a patient can be diagnosed at this stage, it is possible to treat or delay Alzheimer's disease. Resting-state functional magnetic resonance imaging (fMRI) is very common in the process of diagnosing Alzheimer's disease. In th...

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Connectivity networks have been recently used for classification of neurodegenerative diseases, e.g., mild cognitive impairment (MCI). In typical connectivity network-based classification, features are often extracted from (multiple) connectivity networks and concatenated into a long vector for subsequent feature selection and classification. However, some useful network topological information...

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ژورنال

عنوان ژورنال: Human Brain Mapping

سال: 2013

ISSN: 1065-9471

DOI: 10.1002/hbm.22353