Neurology

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

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Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface.

Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been de...

Global brain analysis of minor hallucinations in Parkinson's disease using EEG and MRI data.

INTRODUCTION: Visual hallucination is a prevalent psychiatric disorder characterized by the occurren...

User identification system based on 2D CQT spectrogram of EMG with adaptive frequency resolution adjustment.

User identification systems based on electromyogram (EMG) signals, generated inside the body in diff...

Dual statistical models link baseline visual attention measure to risk for significant symptomatic concussion in sports.

AIM: Athletic pre-season testing can establish functional baseline for comparison following concussi...

Antifungal activity of eumelanin-inspired indoylenepheyleneethynylene against .

is an opportunistic fungal pathogen that causes meningitis in >152,000 immunocompromised individual...

Self-Balancing Exoskeleton Robots Designed to Facilitate Multiple Rehabilitation Training Movements.

This study presents the biomimetic design of the structure and controller of AutoLEE-II, a self-bala...

Rehabilitation Evaluation of Upper Limb Motor Function for Stroke Patients Based on Belief Rule Base.

In the process of rehabilitation treatment for stroke patients, rehabilitation evaluation is a signi...

A continuous-time neurodynamic approach in matrix form for rank minimization.

This article proposes a continuous-time neurodynamic approach for solving the rank minimization unde...

Deep learning-based cerebral aneurysm segmentation and morphological analysis with three-dimensional rotational angiography.

BACKGROUND: The morphological assessment of cerebral aneurysms based on cerebral angiography is an e...

Cross-User Electromyography Pattern Recognition Based on a Novel Spatial-Temporal Graph Convolutional Network.

With the goal of promoting the development of myoelectric control technology, this paper focuses on ...

Morphology-based molecular classification of spinal cord ependymomas using deep neural networks.

Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types ...

A novel ventriculoperitoneal shunt flow sensor based on electrically induced spatial variation in cerebrospinal fluid charge density.

Ventriculoperitoneal (VP) shunts divert cerebrospinal fluid (CSF) out of cerebral ventricles in pat...

Estimating dementia risk in an African American population using the DCTclock.

The prevalence of Alzheimer's disease (AD) and related dementias (ADRD) is increasing. African Ameri...

The expert's knowledge combined with AI outperforms AI alone in seizure onset zone localization using resting state fMRI.

We evaluated whether integration of expert guidance on seizure onset zone (SOZ) identification from ...

Distributed continuous-time accelerated neurodynamic approaches for sparse recovery via smooth approximation to L-minimization.

This paper develops two continuous-time distributed accelerated neurodynamic approaches for solving ...

Deep insights into MCI diagnosis: A comparative deep learning analysis of EEG time series.

BACKGROUND: Individuals in the early stages of Alzheimer's Disease (AD) are typically diagnosed with...

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