Neurology

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

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Semiology Extraction and Machine Learning-Based Classification of Electronic Health Records for Patients With Epilepsy: Retrospective Analysis.

BACKGROUND: Obtaining and describing semiology efficiently and classifying seizure types correctly a...

Amaurosis after Inferior Alveolar Nerve Block Injection in a Seven-Year-Old Girl: A Case Report and Review of the Literature.

A seven-year-old girl was referred for the treatment of her primary teeth. An inferior alveolar nerv...

Real-time sub-milliwatt epilepsy detection implemented on a spiking neural network edge inference processor.

Analyzing electroencephalogram (EEG) signals to detect the epileptic seizure status of a subject pre...

Artificial intelligence-assisted oculo-gait measurements for cognitive impairment in cerebral small vessel disease.

INTRODUCTION: Oculomotor and gait dysfunctions are closely associated with cognition. However, oculo...

Enhancing Radiologists' Performance in Detecting Cerebral Aneurysms Using a Deep Learning Model: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL)-based model for detecting...

Graph neural networks for electroencephalogram analysis: Alzheimer's disease and epilepsy use cases.

Electroencephalography (EEG) is widely used as a non-invasive technique for the diagnosis of several...

Artificial neural network-based prediction of multiple sclerosis using blood-based metabolomics data.

Multiple sclerosis (MS) remains a challenging neurological condition for diagnosis and management an...

Boolean Computation in Single-Transistor Neuron.

Brain neurons exhibit far more sophisticated and powerful information-processing capabilities than t...

A genetic programming Rician noise reduction and explainable deep learning model for Alzheimer's diseases severity prediction.

BACKGROUND: Degradation of magnetic resonance imaging (MRI) remains a challenging issue, with noise ...

Inspiration from Visual Ecology for Advancing Multifunctional Robotic Vision Systems: Bio-inspired Electronic Eyes and Neuromorphic Image Sensors.

In robotics, particularly for autonomous navigation and human-robot collaboration, the significance ...

An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket.

Early screening for Mild Cognitive Impairment (MCI) is crucial in delaying cognitive deterioration a...

Comparative Scoping Review: Robot-Assisted Upper Limb Stroke Rehabilitation in Low- and Middle-Income Countries Versus High-Income Nations.

OBJECTIVE: To examine robotic interventions for upper limb rehabilitation poststroke, focusing on ge...

Evaluating retinal blood vessels for predicting white matter hyperintensities in ischemic stroke: A deep learning approach.

OBJECTIVE: This study aims to investigate whether a deep learning approach incorporating retinal blo...

Analysis of ChatGPT in the Triage of Common Spinal Complaints.

BACKGROUND: ChatGPT is a natural language processing chatbot with a significant prevalence in modern...

Machine learning models for predicting treatment response in infantile epilepsies.

UNLABELLED: Epilepsy stands as one of the prevalent and significant neurological disorders, represen...

Trends in brain MRI and CP association using deep learning.

Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functi...

Neuroscientific insights about computer vision models: a concise review.

The development of biologically-inspired computational models has been the focus of study ever since...

Deep convolutional neural network-based identification and biological evaluation of MAO-B inhibitors.

Parkinson's disease (PD) is one of the most prominent motor disorder of adult-onset dementia connect...

ChatGPT M.D.: Is there any room for generative AI in neurology?

ChatGPT, a general artificial intelligence, has been recognized as a powerful tool in scientific wri...

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