Latest AI and machine learning research in neurology for healthcare professionals.
BACKGROUND CONTEXT: Radiomics, a technique employing machine learning (ML) to extract quantitative features from processed radiographic images, holds promise for improving clinical prediction models. It offers the potential to comprehensively characterize spinal shape and alignment. We hypothesized that processed image (PrIm) algorithms outperform traditional radiographic measurements (TRM) and sc...
BACKGROUND: Electroencephalogram (EEG) microstates reflect momentary localized brain activity and may indicate spontaneous fluctuations within large-scale neural networks. Methamphetamine use disorder (MUD) and obsessive-compulsive disorder (OCD) exhibit overlapping compulsive features, however, similarities or differences in whole-brain dynamics on subsecond timescales between patients with MUD a...
BACKGROUND AND OBJECTIVES: Middle meningeal artery (MMA) embolization is an emerging treatment option for chronic subdural hematoma. Surgeons must pay...
OBJECTIVES: To present a publicly available deep learning-based torso segmentation model that provides comprehensive voxel-wise coverage, including de...
Advancements in artificial intelligence have propelled affective computing toward unprecedented accuracy and real-world impact. By leveraging the uniq...
BACKGROUND: This scoping review highlights major advances and persisting gaps in robotic and AI-driven rehabilitation for stroke, evaluating their imp...
BACKGROUND AND OBJECTIVE: Multidrug-resistant urinary tract infections (MDR UTIs) are a growing concern in patients with brain and spinal cord injurie...
BACKGROUND AND OBJECTIVES: Patient-reported outcome measures (PROMs) are ubiquitously used to assess surgical success after surgery for lumbar spinal ...
Early diagnosis of Alzheimer's disease (AD) requires blood biomarker tests sensitive to femtogram/mL concentrations. Graphene field-effect transistors...
BACKGROUND: Opioid addiction is a major public health concern, associated with numerous health and social problems. Conventional diagnostic methods fo...
Frontotemporal dementia (FTD) presents a complex spectrum of neurodegenerative disorders, encompassing distinct subtypes with varied clinical manifest...
BACKGROUND: This study identified complex, multidimensional, longitudinal biopsychosocial (BPS) phenotypes (MLBPSPs) in people with HIV (PWH) and eval...
Abstracted from the way spiking neurons transmit and process information, spiking neural P systems (SNP systems) are becoming increasingly popular as ...
Anesthesia is a cornerstone of modern surgical practice, enabling interventions by deliberately modulating nociception and consciousness-from localize...
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by significant clinicopathologic heterogeneity. Th...
BACKGROUND: Traumatic Brain Injury (TBI) is a global health concern, with mild TBI (mTBI) being the most common form. Despite its prevalence, accurate...
Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect d...
Traditional repair methods for peripheral neuropathies, such as autologous and allogeneic nerve grafts, face limitations, while peripheral nerve regen...
The voltage-gated sodium channel Nav1.6, encoded by the sodium voltage-gated channel alpha subunit 8 gene, is a crucial regulator of neuronal excitabi...
Deep learning has shown promise in motor imagery-based electroencephalogram (MI-EEG) decoding, a critical task in non-invasive brain-computer interfac...