Neurology

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

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IT: An interpretable transformer model for Alzheimer's disease prediction based on PET/MR images.

Alzheimer's disease (AD) represents a significant challenge due to its progressive neurodegenerative...

Using machine learning to investigate the influence of the prenatal chemical exposome on neurodevelopment of young children.

Research investigating the prenatal chemical exposome and child neurodevelopment has typically focus...

AI-Driven Information for Relatives of Patients with Malignant Middle Cerebral Artery Infarction: A Preliminary Validation Study Using GPT-4o.

This study examines GPT-4o's ability to communicate effectively with relatives of patients undergoi...

An integrated microfluidic and fluorescence platform for probing in vivo neuropharmacology.

Neurotechnologies and genetic tools for dissecting neural circuit functions have advanced rapidly ov...

CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection,...

Artificial intelligence for the detection of interictal epileptiform discharges in EEG signals.

INTRODUCTION: Over the past decades, the integration of modern technologies - such as electronic hea...

Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.

This study aims to compare brain activity differences under the motor imagery-brain-computer interfa...

MXene-enabled organic synaptic fiber for ultralow-power and biochemical-mediated neuromorphic transistor.

Fibrous bioelectronic provides an intrinsically accessible platform for artificial nerve and real-ti...

Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks.

Multimodal neuroimaging data modeling has become a widely used approach but confronts considerable c...

Semantic-consistent diffusion model for unsupervised traumatic brain injury detection and segmentation from computed tomography images.

BACKGROUND: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment ...

Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.

Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by...

Advances in MRI optic nerve segmentation.

Understanding optic nerve structure and monitoring changes within it can provide insights into neuro...

Development and validation of Prediction models for radiation-induced hypoglossal neuropathy in patients with nasopharyngeal carcinoma.

BACKGROUND AND PURPOSE: To establish predictive models for radiation-induced hypoglossal neuropathy ...

Optical Synaptic Devices with Multiple Encryption Features Based on SERS-Revealed Charge-Transfer Mechanism.

2D optical synaptic devices with atomic-scale thickness show potential for building highly integrate...

Fast, accurate, and versatile data analysis platform for the quantification of molecular spatiotemporal signals.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biologi...

NeuroNasal: Advanced AI-Driven Self-Supervised Learning Approach for Enhanced Sinonasal Pathology Detection.

Sinus diseases are inflammations or infections of the sinuses that significantly impact patient qual...

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