Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging

AbstractA fundamental problem of supervised learning algorithms for brain imaging applications is that the number of features far exceeds the number of subjects. In this paper, we propose a combined feature selection and extraction approach for multiclass problems. This method starts with a bagging procedure which calculates the sign consistency of the multivariate analysis (MVA) projection matrix feature-wise to determine the relevance of each feature. This relevance measure provides a parsimonious matrix, which is combined with a hypothesis test to automatically determine the number of selected features. Then, a novel MVA regularized with the sign and magnitude consistency of the features is used to generate a reduced set of summary components providing a compact data description. We evaluated the proposed method with two multiclass brain imaging problems: 1) the classification of the elderly subjects in four classes (cognitively normal, stable mild cognitive impairment (MCI), MCI converting to AD in 3 years, and Alzheimer ’s disease) based on structural brain imaging data from the ADNI cohort; 2) the classification of children in 3 classes (typically developing, and 2 types of Attention Deficit/Hyperactivity Disorder (ADHD)) based on functional connectivity. Experimental results confirmed that each brain image (def ined by 29.852 features in the ADNI database and 61.425 in the ADHD) could be represented with only 30 − 45% of the original features. Furthermore, ...
Source: Neuroinformatics - Category: Neuroscience Source Type: research

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CONCLUSIONS: Our results suggest a significant, inverse association between SLC2A3 rs12842 and the risk of AD. PMID: 32627711 [PubMed - as supplied by publisher]
Source: Neurological Research - Category: Neurology Tags: Neurol Res Source Type: research
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Source: International Journal of Environmental Research and Public Health - Category: Environmental Health Authors: Tags: Review Source Type: research
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Source: Ageing Research Reviews - Category: Genetics & Stem Cells Authors: Tags: Ageing Res Rev Source Type: research
Abstract In recent years, the roles of astrocytes of the central nervous system in brain function and neurological disease have drawn increasing attention. As a member of the N-myc downstream-regulated gene (NDRG) family, NDRG2 is principally expressed in astrocytes of the central nervous system. NDRG2, which is involved in cell proliferation and differentiation, is commonly regarded as a tumor suppressor. In astrocytes, NDRG2 affects the regulation of apoptosis, astrogliosis, blood-brain barrier integrity, and glutamate clearance. Several preclinical studies have revealed that NDRG2 is implicated in the pathogene...
Source: Cellular and Molecular Life Sciences : CMLS - Category: Cytology Authors: Tags: Cell Mol Life Sci Source Type: research
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Source: International Journal of Developmental Neuroscience - Category: Neuroscience Authors: Tags: Int J Dev Neurosci Source Type: research
Authors: Youssef P, Nath S, Chaimowitz GA, Prat SS Abstract This review aims to consolidate the available information on use of electroretinography as a diagnostic tool in psychiatry. The electroretinogram (ERG) has been found to have diagnostic utility in cocaine withdrawal (reduced light-adapted b-wave response), major depressive disorder (reduced contrast gain in pattern ERG), and schizophrenia (reduced a- and b-wave amplitudes). This review examines these findings as well as the applicability of ERG to substance use disorder, Alzheimer's disease, autism spectrum disorder, panic disorder, eating disorders, atten...
Source: Journal of the Association of European Psychiatrists - Category: Psychiatry Tags: Eur Psychiatry Source Type: research
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Source: Chemosphere - Category: Chemistry Authors: Tags: Chemosphere Source Type: research
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Source: Journal of Innovative Optical Health Sciences - Category: Biomedical Science Authors: Source Type: research
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Source: Progress in Retinal and Eye Research - Category: Opthalmology Source Type: research
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Source: Journal of Medical Systems - Category: Information Technology Source Type: research
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