Neurology

Multimodal CT-based imaging biomarkers for mechanical reperfusion in acute ischemic stroke.

Mechanical thrombectomy (MT) has emerged as the primary treatment for restoring blood flow in acute ...

Bone Mineral Density of Spine Patients with CT Hounsfield Units and AI Segmentation: A Contemporary Review.

It is widely accepted that bone mineral density affects outcomes for spinal arthrodesis surgeries. T...

Predicting gait kinematics in youth with cerebral palsy using clinically informed machine learning algorithms.

BACKGROUND: Gait deviations are common in youth with Cerebral Palsy (CP), with the change in gait pa...

The cerebro-cerebellar system: Integrative roles in motor control, cognition, and neuropsychiatric disorders.

The cerebro-cerebellar system, a network of bidirectional loops between the cerebellum and cerebral ...

Deep Learning-Driven Transmission Electron Microscopy Analysis of Murine Optic Nerve Myelinated Axons.

OBJECTIVE: To develop and validate a deep learning-based method for automated quantification of reti...

Proteomic profile of CSF obtained at the time of diagnosis determines amyotrophic lateral sclerosis progression and survival: CXCL7 levels in disease prognosis and survival.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease primarily affecting motor n...

Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.

The validation of promising clinical biomarkers, molecular mechanisms, and novel drug targets in car...

The role of ionotropic glutamate receptors in Alzheimer's disease: A scientometric analysis.

BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyl...

A CNN-transformer fusion for EEG-based discrimination of Alzheimer's and frontotemporal dementia.

Dementia is a progressive neurodegenerative disorder that severely impacts cognitive functions and d...

WGB-GLFI: A Novel Graph-Based Global-Local Feature Interaction Framework for Automated Seizure Detection.

Epilepsy detection faces significant challenges due to unpredictable seizures, ranging from brief aw...

Impedance Myography Circle Mapping: A Geometry-Based Multi-Frequency EIM Framework for Quantitative Assessment of Post-Stroke Muscle Impairment.

Post-stroke neuromuscular impairment arises from heterogeneous structural and electrophysiological a...

ICP-WAVES: Intracranial Pressure Waveform Analysis and Visualization for Enhanced Signal Processing.

OBJECTIVE: Intracranial pressure (ICP) waveform morphology reflects brain compliance and cerebrospin...

Multimodal Wearable Sensor-Based Stress Detection: Machine Learning Pipeline with Systematic Feature Selection and Key Biomarker Insights.

The increasing awareness of stress-related health impacts has driven demand for accurate, non-invasi...

Attention-enhanced deep learning model for automated classification of hemorrhagic and ischemic stroke on CT imaging.

BACKGROUND: Stroke is a disease with extremely high mortality and disability rates worldwide. Hemorr...

The value of triglyceride-glucose-body shape index (TyG-ABSI) in evaluating stroke: a multi-centre cross-sectional study.

BACKGROUND: Stroke is the second leading cause of disability and mortality worldwide. A body shape i...

Elucidating biopsychosocial mechanisms in migraine: an integrative analytics approach combining genetics, neuroimaging, and machine learning.

BACKGROUND: Migraine is a complex and disabling neurological disorder shaped by the interplay of bio...

A novel framework for cognitive state identification using resting-state EEG.

Recent advancements in cognitive impairment research have led to significant progress. Electroenceph...

ARIMA-based forecasting of cerebral physiologic signals in acute traumatic brain injury: a CAnadian high-resolution TBI (CAHR-TBI) cohort study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health issue, with limited progress ...

M[Formula: see text]DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson's disease(PD) progression using whole-blood RNA sequencing data.

With emerging single-cell transcriptomics data, deep learning approaches have enabled the diagnosis ...

Integrating attractor dynamics and connectivity features for EEG-based dementia classification.

The research progress of wearable digital health technologies in epilepsy management.

Epilepsy is one of the most common neurological disorders, characterized by recurrent, unpredictable...