Neurology

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

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Deep learning-based auditory attention decoding in listeners with hearing impairment.

This study develops a deep learning (DL) method for fast auditory attention decoding (AAD) using ele...

DMA-HPCNet: Dual Multi-Level Attention Hybrid Pyramid Convolution Neural Network for Alzheimer's Disease Classification.

Computer-aided diagnosis (CAD) plays a crucial role in the clinical application of Alzheimer's disea...

Enhancing voxel-based dosimetry accuracy with an unsupervised deep learning approach for hybrid medical image registration.

BACKGROUND: Deformable registration is required to generate a time-integrated activity (TIA) map whi...

Embedded Machine Learning System for Muscle Patterns Detection in a Patient with Shoulder Disarticulation.

The integration of artificial intelligence (AI) models in the classification of electromyographic (E...

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantia...

Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance.

Neural circuits with specific structures and diverse neuronal firing features are the foundation for...

Robot-assisted gait training improves walking and cerebral connectivity in children with unilateral cerebral palsy.

BACKGROUND: Robot-assisted gait training (RAGT) is promising to help walking rehabilitation in cereb...

A novel feature extraction method PSS-CSP for binary motor imagery - based brain-computer interfaces.

In order to improve the performance of binary motor imagery (MI) - based brain-computer interfaces (...

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, a...

A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children.

OBJECTIVE: Common pain assessment approaches such as self-evaluation and observation scales are inap...

Predictive modelling and identification of key risk factors for stroke using machine learning.

Strokes are a leading global cause of mortality, underscoring the need for early detection and preve...

TASA: Temporal Attention With Spatial Autoencoder Network for Odor-Induced Emotion Classification Using EEG.

The olfactory system enables humans to smell different odors, which are closely related to emotions....

Deploying Robot-Led Activities for People with Dementia at Aged Care Facilities: A Feasibility Study.

OBJECTIVES: To explore the feasibility of deploying robot-led activities for people with dementia li...

Alzheimer's disease early screening and staged detection with plasma proteome using machine learning and convolutional neural network.

Alzheimer's disease (AD) stands as the prevalent progressive neurodegenerative disease, precipitatin...

Parkinson's Disease Recognition Using Decorrelated Convolutional Neural Networks: Addressing Imbalance and Scanner Bias in rs-fMRI Data.

Parkinson's disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells...

Performance Metrics, Algorithms, and Applications of Artificial Intelligence in Vascular and Interventional Neurology: A Review of Basic Elements.

Artificial intelligence (AI) is currently being used as a routine tool for day-to-day activity. Medi...

The independence of impairments in proprioception and visuomotor adaptation after stroke.

BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor r...

Investigating the discrimination ability of 3D convolutional neural networks applied to altered brain MRI parametric maps.

Convolutional neural networks (CNNs) are gradually being recognized in the neuroimaging community as...

Implications of Large Language Models for Quality and Efficiency of Neurologic Care: Emerging Issues in Neurology.

Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recogni...

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