AIMC Topic: Gray Matter
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Prediction of depressive symptoms severity based on sleep quality, anxiety, and gray matter volume: a generalizable machine learning approach across three datasets.
EBioMedicine
Sep 9, 2024
BACKGROUND: Depressive symptoms are rising in the general population, but their associated factors are unclear. Although the link between sleep disturbances and depressive symptoms severity (DSS) is reported, the predictive role of sleep on DSS and t...
Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases.
Acta neuropathologica communications
Aug 17, 2024
Accurate and scalable quantification of amyloid-β (Aβ) pathology is crucial for deeper disease phenotyping and furthering research in Alzheimer Disease (AD). This multidisciplinary study addresses the current limitations on neuropathology by leveragi...
Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning.
Autism research : official journal of the International Society for Autism Research
Jun 24, 2024
Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter bra...
sMRI-ADNet: an interpretable deep learning framework integrating Euclidean-graph representations of Alzheimer's disease solely from structural MRI.
Magma (New York, N.Y.)
Jun 13, 2024
OBJECTIVE: To establish a multi-dimensional representation solely on structural MRI (sMRI) for early diagnosis of AD.
Analysis of Cerebral CT Based on Supervised Machine Learning as a Predictor of Outcome After Out-of-Hospital Cardiac Arrest.
Neurology
Jun 10, 2024
BACKGROUND AND OBJECTIVES: In light of limited intensive care capacities and a lack of accurate prognostic tools to advise caregivers and family members responsibly, this study aims to determine whether automated cerebral CT (CCT) analysis allows pro...
Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity.
NeuroImage
Jun 7, 2024
Brain disorders are often associated with changes in brain structure and function, where functional changes may be due to underlying structural variations. Gray matter (GM) volume segmentation from 3D structural MRI offers vital structural informatio...
Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.
Journal of affective disorders
May 31, 2024
BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presenta...
Neuroimaging Insights: Structural Changes and Classification in Ménière's Disease.
Ear and hearing
May 24, 2024
OBJECTIVES: This study aimed to comprehensively investigate the neuroanatomical alterations associated with idiopathic Ménière's disease (MD) using voxel-based morphometry and surface-based morphometry techniques. The primary objective was to explore...
Machine learning models for diagnosis of essential tremor and dystonic tremor using grey matter morphological networks.
Parkinsonism & related disorders
Apr 28, 2024
BACKGROUND: Essential tremor (ET) and dystonic tremor (DT) are the two most common tremor disorders, and misdiagnoses are very common due to similar tremor symptoms. In this study, we explore the structural network mechanisms of ET and DT using brain...
Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features.
GeroScience
Apr 26, 2024
To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers that can accurately capture age-related biological changes in the human brain. Brain serotonin 2A r...
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