Latest AI and machine learning research in neurology for healthcare professionals.
Huntington's disease (HD) is a complex neurodegenerative disorder with considerable heterogeneity in clinical manifestations. While CAG repeat length is a known predictor of disease severity, this heterogeneity suggests the involvement of additional genetic and environmental factors. Previously we revealed that HD primary fibroblasts exhibit unique features, including distinct nuclear morphology a...
Alzheimer's disease (AD) is a chronic neurodegenerative disease. Early diagnosis are very important to timely treatment and delay the progression of the disease. In the past decade, many computer-aided diagnostic (CAD) algorithms have been proposed for classification of AD. In this paper, we propose a novel graph neural network method, termed Brain Graph Attention Network (BGAN) for classification...
Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing thes...
We conducted a multicenter and retrospective study to describe the use of botulinum toxin type A (BoNT-A) to treat post-stroke spasticity (PSS). Data ...
Stroke is a severe medical condition which may lead to permanent disability conditions. The initial 8Â weeks following a stroke are crucial for rehabil...
BACKGROUND: Optic neuritis (ON) is a complex clinical syndrome that has diverse etiologies and treatments based on its subtypes. Notably, ON associate...
With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a ...
Several (inter)national longitudinal dementia observational datasets encompassing demographic information, neuroimaging, biomarkers, neuropsychologica...
Cerebral aneurysms, affecting 2-5% of the global population, are often asymptomatic and commonly located within the Circle of Willis. A recent study i...
Analyses of complex behaviors of Cerebrospinal Fluid (CSF) have become increasingly important in diseases diagnosis. The changes of the phase-contrast...
Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in c...
This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter h...
Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive impairment (MCI) and increase the risk of progression...
Epilepsy claims the lives of many people, so researchers strive to build highly accurate diagnostic models. One of the limitations of obtaining high a...
Motor imagery (MI) represents one major paradigm of Brain-computer interfaces (BCIs) in which users rely on their electroencephalogram (EEG) signals t...
BACKGROUND: Transcranial sonography (TCS) plays a crucial role in diagnosing Parkinson's disease. However, the intricate nature of TCS pathological fe...
The human brain operates at multiple levels, from molecules to circuits, and understanding these complex processes requires integrated research effort...
Over the past decade, the intricacies of sports-related concussions among female athletes have become readily apparent. Traditional clinical methods f...
. Monitoring the depth of anaesthesia (DOA) during surgery is of critical importance. However, during surgery electroencephalography (EEG) is usually ...
Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient fo...