AIMC Topic: Gray Matter

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Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

Scientific reports May 20, 2020
To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjust...
Case-Control Studies Diabetes Mellitus, Type 2 Glomerular Filtration Rate Follow-Up Studies Cross-Sectional Studies Male Cardiovascular Diseases Middle Aged Germany Gray Matter Prediabetic State Life Style Machine Learning Confounding Factors, Epidemiologic Magnetic Resonance Imaging Prospective Studies Models, Neurological Female Organ Size Linear Models Humans
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Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions.

Annals of clinical and translational neurology Apr 18, 2020
OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterog...
Aged Adult Sensitivity and Specificity Male Humans Female White Matter Diffusion Tensor Imaging Diffusion Magnetic Resonance Imaging Middle Aged Deep Learning Multiple Sclerosis Gray Matter
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Application of Generalized Split Linearized Bregman Iteration algorithm for Alzheimer's disease prediction.

Aging Apr 5, 2020
In this paper, we applied a novel method for the detection of Alzheimer's disease (AD) based on a structural magnetic resonance imaging (sMRI) dataset. Specifically, the method involved a new classification algorithm of machine learning, named Genera...
Humans Machine Learning Organ Size Predictive Value of Tests Alzheimer Disease Neuroimaging Aged Algorithms Gray Matter Male Prognosis Middle Aged Female Magnetic Resonance Imaging Reproducibility of Results
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A novel CNN based Alzheimer's disease classification using hybrid enhanced ICA segmented gray matter of MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 28, 2020
Predicting Alzheimer's Disease (AD) from Mild Cognitive Impairment (MCI) and Cognitive Normal (CN) has become wide. Recent advancement in neuroimaging in adoption with machine learning techniques are especially useful for pattern recognition of medic...
Image Interpretation, Computer-Assisted Early Diagnosis Neuroimaging Humans Gray Matter Neural Networks, Computer Diagnosis, Computer-Assisted Alzheimer Disease
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A comparison of fMRI and behavioral models for predicting inter-temporal choices.

NeuroImage Feb 18, 2020
In an inter-temporal choice (IteCh) task, subjects are offered a smaller amount of money immediately or a larger amount at a later time point. Here, we are using trial-by-trial fMRI data from 363 recording sessions and machine learning in an attempt ...
Delay Discounting Psychomotor Performance Gray Matter Models, Psychological Adolescent Development Models, Theoretical Support Vector Machine Follow-Up Studies Magnetic Resonance Imaging Male Functional Neuroimaging Adolescent Humans Female
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Identification of patients with and without minimal hepatic encephalopathy based on gray matter volumetry using a support vector machine learning algorithm.

Scientific reports Feb 12, 2020
Minimal hepatic encephalopathy (MHE) is characterized by diffuse abnormalities in cerebral structure, such as reduced cortical thickness and altered brain parenchymal volume. This study tested the potential of gray matter (GM) volumetry to differenti...
Gray Matter Hepatic Encephalopathy Humans Female Adult Male Middle Aged Support Vector Machine Magnetic Resonance Imaging
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Morphological Neuroimaging Biomarkers for Tinnitus: Evidence Obtained by Applying Machine Learning.

Neural plasticity Dec 13, 2019
According to previous studies, many neuroanatomical alterations have been detected in patients with tinnitus. However, the results of these studies have been inconsistent. The objective of this study was to explore the cortical/subcortical morphologi...
Magnetic Resonance Imaging Tinnitus Neuroimaging Gray Matter Machine Learning Young Adult Humans Biomarkers Adult Brain Male Female Middle Aged
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Multiple Holdouts With Stability: Improving the Generalizability of Machine Learning Analyses of Brain-Behavior Relationships.

Biological psychiatry Dec 10, 2019
BACKGROUND: In 2009, the National Institute of Mental Health launched the Research Domain Criteria, an attempt to move beyond diagnostic categories and ground psychiatry within neurobiological constructs that combine different levels of measures (e.g...
Gray Matter Humans Mood Disorders National Institute of Mental Health (U.S.) Machine Learning Brain United States
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Disentangling brain functional network remodeling in corticobasal syndrome - A multimodal MRI study.

NeuroImage. Clinical Dec 2, 2019
OBJECTIVE: The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimo...
Female Aged Male Middle Aged Multimodal Imaging Neuroimaging Gray Matter Support Vector Machine Magnetic Resonance Imaging Cerebral Cortex Humans Connectome Nerve Net Basal Ganglia Diseases
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Integrating machining learning and multimodal neuroimaging to detect schizophrenia at the level of the individual.

Human brain mapping Nov 18, 2019
Schizophrenia is a severe psychiatric disorder associated with both structural and functional brain abnormalities. In the past few years, there has been growing interest in the application of machine learning techniques to neuroimaging data for the d...
Connectome Neural Pathways Humans Diffusion Tensor Imaging Machine Learning Rest Female Neuroimaging Image Processing, Computer-Assisted Reproducibility of Results Young Adult Gray Matter Support Vector Machine Magnetic Resonance Imaging Adult White Matter Multimodal Imaging Male Schizophrenia Middle Aged
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