Neurology

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

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Using Natural Language Processing (GPT-4) for Computed Tomography Image Analysis of Cerebral Hemorrhages in Radiology: Retrospective Analysis.

BACKGROUND: Cerebral hemorrhage is a critical medical condition that necessitates a rapid and precis...

Real-world application of a 3D deep learning model for detecting and localizing cerebral microbleeds.

BACKGROUND: Detection and localization of cerebral microbleeds (CMBs) is crucial for disease diagnos...

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative a...

Machine Learning Based Prediction of Imminent ICP Insults During Neurocritical Care of Traumatic Brain Injury.

BACKGROUND: In neurointensive care, increased intracranial pressure (ICP) is a feared secondary brai...

Float like a butterfly, swim like a biohybrid neuromuscular robot.

A butterfly-like robot swims using an electronic device to stimulate human-derived motor neurons and...

Wirelessly steerable bioelectronic neuromuscular robots adapting neurocardiac junctions.

Biological motions of native muscle tissues rely on the nervous system to interface movement with th...

Subject-Independent Wearable P300 Brain-Computer Interface Based on Convolutional Neural Network and Metric Learning.

The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user...

Can robots lie? A posthumanist approach to robotic animals and deceptive practices in dementia care.

Robotic animals are designed to resemble real, living animals, but at the same time, dementia care g...

Classification of cyclic alternating patterns of sleep using EEG signals.

Cyclic alternating patterns (CAP) occur in electroencephalogram (EEG) signals during non-rapid eye m...

Multi-source Selective Graph Domain Adaptation Network for cross-subject EEG emotion recognition.

Affective brain-computer interface is an important part of realizing emotional human-computer intera...

3-1-3 Weight averaging technique-based performance evaluation of deep neural networks for Alzheimer's disease detection using structural MRI.

Alzheimer's disease (AD) is a progressive neurological disorder. It is identified by the gradual shr...

Early diagnosis of Alzheimer's Disease based on multi-attention mechanism.

Alzheimer's Disease is a neurodegenerative disorder, and one of its common and prominent early sympt...

Integrating large language models in care, research, and education in multiple sclerosis management.

Use of techniques derived from generative artificial intelligence (AI), specifically large language ...

A Compact Graph Convolutional Network With Adaptive Functional Connectivity for Seizure Prediction.

Seizure prediction using EEG has significant implications for the daily monitoring and treatment of ...

Optimizing Real-Time MI-BCI Performance in Post-Stroke Patients: Impact of Time Window Duration on Classification Accuracy and Responsiveness.

Brain-computer interfaces (BCIs) are promising tools for motor neurorehabilitation. Achieving a bala...

Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis.

BACKGROUND AND OBJECTIVES: to identify predictors of progression to refractory status epilepticus (R...

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