Latest AI and machine learning research in neurology for healthcare professionals.
PURPOSE OF REVIEW: Neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have been linked to environmental exposures, yet the underlying neurobiological mechanisms remain poorly understood. Magnetic resonance imaging (MRI) offers an important in vivo tool for examining how environmental neurotoxicants impact brain development...
Neuroimaging plays a critical role in the diagnosis of Alzheimer's disease (AD), with Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) providing detailed structural and functional information for deep learning (DL) based classification. However, their high cost and limited availability restrict widespread clinical use. Computed Tomography (CT), while affordable and widely ac...
Neutrophil extracellular traps are implicated in immunothrombosis and neuroinflammation in ischemic stroke, but blood-based markers that distinguish s...
BACKGROUND AND AIMS: Age-related eye diseases (AREDs) share aging as a major risk factor, but the systemic molecular changes preceding disease onset r...
Parkinson's disease (PD) is marked by progressive neurodegeneration in the substantia nigra (SN). This study evaluated deep-learning saturation-transf...
While single-omics analyses of Parkinson's Disease (PD) have demonstrated their ability in revealing the underlying molecular mechanisms, they often f...
Spatial transcriptomics extends traditional transcriptomic methods by quantifying gene expression within intact tissues while preserving each cell's p...
BACKGROUND: Accurately distinguishing minimally conscious state plus (MCS+) from minimally conscious state minus (MCS-) is critical for prognosis and ...
BACKGROUND: MicroRNA (miRNA) biomarker studies in Alzheimer's disease (AD) typically assume monotonic relationships between expression levels and dise...
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Traditional models for estimating AD onset cannot capture nonlinear i...
BACKGROUND: Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy of the hand. While carpal tunnel release surgery generally provides ...
BACKGROUND: Cancer-related pain is a multidimensional phenomenon, and key determinants of pain intensity remain unclear. The aim of this study was to ...
The present manuscript provides a comprehensive overview of neural stem cell (NSC)-derived extracellular vesicles (NSC-EVs( as a cell-free approach to...
Motor imagery (MI) has emerged as a pivotal paradigm in non-invasive brain-computer interfaces (BCIs) for neurorehabilitation, enabling motor function...
Event-related potential (ERP), a specialized paradigm of electroencephalographic (EEG), reflects neurological responses to external stimuli or events,...
ABSTRACT: In the past 20 years, magnetic resonance neurography has evolved from an experimental technique into an essential diagnostic pillar for peri...
BACKGROUND: Artificial intelligence has previously demonstrated the capability to interpret cervical spine imaging. The present study aims to identify...
BACKGROUND: Substantial variability in individual responses to intermittent theta-burst stimulation (iTBS) limits its clinical efficacy, yet neurophys...
Accurately predicting which individuals with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD) can improve patient care. This ...
Rapid eye movement (REM) sleep behaviour disorder (RBD), particularly its idiopathic/isolated form (iRBD), is a prodromal marker for α-synucleinopathi...