Latest AI and machine learning research in neurology for healthcare professionals.
IntroductionEEGLAB is a widely used software for analyzing electroencephalography (EEG) datasets, with over 20 years of global use. This bibliometric study investigates EEGLAB publications in the Asia-Pacific and Arabian regions, focusing on Scopus and Web of Science (WoS) indexed sources, to understand regional contributions and trends in EEG research across 80 countries and territories.MethodsBi...
PURPOSE: Digital Subtraction Angiography (DSA) is an X-ray-based imaging modality intimately related to minimally invasive procedures in interventional radiology, cardiology, vascular and neurologic surgery. Emulating tomographic methods like 3D vessel reconstruction and flat-panel detector CT perfusion imaging increases its diagnostic utility. This study demonstrates a hardware and software setup...
Engineered three-dimensional (3D) neural constructs hold significant promise for repairing neural tissue damage and recapitulating the human brain in ...
Multi-electrode recording of neuronal activity in cultures offer opportunities for understanding how the structure of a network gives rise to function...
Stroke is a leading cause of mortality worldwide, with hypertension being its most significant risk factor. However, few studies have specifically dev...
BACKGROUND: Childhood trauma (CT) is a major risk factor for adolescent major depressive disorder (MDD), yet its neurobiological underpinnings and lon...
UNLABELLED: This study aims to evaluate the reliability, quality, and readability of ChatGPT-4's responses to questions about cerebral palsy (CP) and ...
Radiologically Isolated Syndrome (RIS) is characterized by incidental MRI findings indicative of multiple sclerosis (MS) in asymptomatic individuals. ...
Drug-infused foods are increasingly encountered in forensic investigations, including drug-facilitated crimes (DFC), chemical submission cases, and th...
BACKGROUND: Traumatic brain injury (TBI) remains a major public health concern, with over 69 million cases annually worldwide. Accurate patient-specif...
Efforts to define biologically grounded subtypes of schizophrenia have increasingly leveraged neuroimaging data and clustering algorithms. Such approa...
Autism Spectrum Disorder (ASD) remains diagnostically challenging due to its neurobiological heterogeneity and the current reliance on subjective beha...
BackgroundEarly diagnosis of dementia is essential for enabling timely interventions that may slow disease progression, improve patient outcomes, and ...
The specific neuroanatomy of mild cognitive impairment (MCI) is obscured by its clinical heterogeneity and confounding effects from normative variatio...
Accurate sleep stage classification in animal models is crucial for translational sleep research, enabling the study of mechanistic pathways and thera...
BACKGROUND: Artificial intelligence (AI) and wearable sensors are increasingly reshaping sports injury risk prediction by enabling continuous, individ...
Wearing-off (WO) is a common motor complication in Parkinson's disease (PD), characterized by the re-emergence of symptoms before the next dose of dop...
Quantifying behavior in animal models is essential for understanding neurological disorders, yet traditional scoring methods often fail to capture the...
The drug development for central nervous system (CNS) disorders, particularly neurodegenerative diseases, such as Alzheimer's disease, Parkinson's dis...
OBJECTIVE: Efficient and high-quality history taking is central to vestibular diagnosis, but it is often constrained by limited consultation time and ...