Neurology

Latest AI and machine learning research in neurology for healthcare professionals.

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A robotic rehabilitation intervention in a home setting during the Covid-19 outbreak: a feasibility pilot study in patients with stroke.

BACKGROUND: Telerehabilitation allows patients to engage in therapy away from healthcare facilities,...

Decoding of lexical items and grammatical features in EEG: A cross-linguistic study.

Diverse evidence supports the theory that bilingual language users have language-invariant represent...

Predictive Analysis of Amyotrophic Lateral Sclerosis Progression and Mortality in a Clinic Cohort From Singapore.

INTRODUCTION: There is currently no comprehensive Amyotrophic Lateral Sclerosis (ALS) patient databa...

Burnout Among Physicians Treating Patients with Multiple Sclerosis in the United States: A Podcast.

Physician burnout, a growing crisis in the healthcare system of the United States of America (USA), ...

Challenges and Opportunities: Nanomaterials in Epilepsy Diagnosis.

Epilepsy is a common neurological disorder characterized by a significant rate of disability. Accura...

AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.

The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions i...

Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.

The neural activity patterns of localized brain regions are crucial for recognizing brain intentions...

HATNet: EEG-Based Hybrid Attention Transfer Learning Network for Train Driver State Detection.

Electroencephalography (EEG) is widely utilized for train driver state detection due to its high acc...

Torg-Pavlov ratio qualification to diagnose developmental cervical spinal stenosis based on HRViT neural network.

BACKGROUND: Developing computer-assisted methods to measure the Torg-Pavlov ratio (TPR), defined as ...

Enhancing motor imagery EEG classification with a Riemannian geometry-based spatial filtering (RSF) method.

Motor imagery (MI) refers to the mental simulation of movements without physical execution, and it c...

Integrating WGCNA and SVM-RFE identifies hub molecular biomarkers driving ischemic stroke progression.

BACKGROUND: Stroke is the second most common cause of death worldwide and the leading cause of long-...

Post-stroke spontaneous motor recovery in mice can be predicted from acute-phase local field potential using machine learning.

Stroke remains a leading cause of long-term disability, underscoring the urgent need for effective p...

Cerebrospinal fluid inflammatory cytokines as prognostic indicators for cognitive decline across Alzheimer's disease spectrum.

BackgroundNeuroinflammation actively contributes to the pathophysiology of Alzheimer's disease (AD);...

A wearable ankle-assisted robot for improving gait function and pattern in stroke patients.

BACKGROUND: Hemiplegic gait after a stroke can result in a decreased gait speed and asymmetrical gai...

Revolutionizing Alzheimer's disease detection with a cutting-edge CAPCBAM deep learning framework.

Early and accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment. While t...

The clinical significance of an AI-based assumption model for neurocognitive diseases using a novel dual-task system.

Dual-task composed of gait or stepping tasks combined with cognitive tasks has been well-established...

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