Neurology

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

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User Experience Evaluation of a Spinal Surgery Robot: Workload, Usability, and Satisfaction Study.

BACKGROUND: Robotic spine surgery has continued to evolve since its US Food and Drug Administration ...

Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

This study aimed to: (1) validate a natural language processing (NLP) system developed for the home ...

Data-driven normative values based on generative manifold learning for quantitative MRI.

In medicine, abnormalities in quantitative metrics such as the volume reduction of one brain region ...

Analysis of guide wire displacement in robot-assisted spinal pedicle screw implantation.

Robot-assisted pedicle screw placement is prone to guide wire migration, and the related influencing...

Recognition of Glaucomatous Fundus Images Using Machine Learning Methods Based on Optic Nerve Head Topographic Features.

PRCIS: Machine learning classifiers are an effective approach to detecting glaucomatous fundus image...

PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.

BACKGROUND: Predicting stroke recurrence for individual patients is difficult, but individualized pr...

Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review.

Parkinson's Disease (PD) is a progressive neurodegenerative illness triggered by decreased dopamine ...

Predicting an EEG-Based hypnotic time estimation with non-linear kernels of support vector machine algorithm.

Our ability to measure time is vital for daily life, technology use, and even mental health; however...

AI-assisted automatic MRI-based tongue volume evaluation in motor neuron disease (MND).

PURPOSE: Motor neuron disease (MND) causes damage to the upper and lower motor neurons including the...

Evaluations of artificial intelligence and machine learning algorithms in neurodiagnostics.

This article evaluates the ethical implications of utilizing artificial intelligence (AI) algorithms...

A machine learning based depression screening framework using temporal domain features of the electroencephalography signals.

Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely a...

Combined brain topological metrics with machine learning to distinguish essential tremor and tremor-dominant Parkinson's disease.

BACKGROUND: Essential tremor (ET) and Parkinson's disease (PD) are the two most prevalent movement d...

Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer's Disease Using Biophysical Modeling and Deep Learning.

Alzheimer's disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and...

Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.

Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to...

Artificial intelligence performance in clinical neurology queries: the ChatGPT model.

INTRODUCTION: The use of artificial intelligence technology is progressively expanding and advancing...

Utilizing Machine Learning to Identify Biomarkers of Endoplasmic Reticulum Stress and Analyze Immune Cell Infiltration in Parkinson's Disease.

The neurodegenerative disorder known as Parkinson's disease (PD) affects many people. The objective ...

Machine learning models help differentiate between causes of recurrent spontaneous vertigo.

BACKGROUND: Vestibular migraine (VM) and Menière's disease (MD) are two common causes of recurrent s...

Deep learning approaches for seizure video analysis: A review.

Seizure events can manifest as transient disruptions in the control of movements which may be organi...

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