AIMC Topic: Gray Matter

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Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

Brain and behavior
BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral...

A multiple hold-out framework for Sparse Partial Least Squares.

Journal of neuroscience methods
BACKGROUND: Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (...

Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease.

International journal of neural systems
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the constr...

Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study.

The American journal of psychiatry
OBJECTIVE: Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect accelerated aging of the brain, or is it caused by a ...

CSF YKL-40 and pTau181 are related to different cerebral morphometric patterns in early AD.

Neurobiology of aging
Cerebrospinal fluid (CSF) concentrations of YKL-40 that serve as biomarker of neuroinflammation are known to be altered along the clinico-biological continuum of Alzheimer's disease (AD). The specific structural cerebral correlates of CSF YKL-40 were...

Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span.

Medical engineering & physics
In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI datase...

Investigating the use of support vector machine classification on structural brain images of preterm-born teenagers as a biological marker.

PloS one
Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM) classification methods we aimed to investigate whether MRI data, collected in adolescence, could be ...

Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM.

Human brain mapping
Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatially segregated brain regions which may be related to both local gray matter (GM) atrophy as well as a decline in the fiber integrity of the underlying ...

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.

NeuroImage
The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6-8 month...

Upper Airway Volume Predicts Brain Structure and Cognition in Adolescents.

American journal of respiratory and critical care medicine
One in 10 children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood. We assessed the relationship between magnetic resonance imaging-derived upper airwa...