Neurology

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

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Deep learning-based classification of hemiplegia and diplegia in cerebral palsy using postural control analysis.

Cerebral palsy (CP) is a neurological condition that affects mobility and motor control, presenting ...

Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion.

Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vi...

Genetically encoded sensors illuminate detection for neurotransmission: Development, application, and optimization strategies.

Limitations in existing tools have hindered neuroscientists from achieving a deeper understanding of...

Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.

BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise predict...

Machine Learning-Based localization of the epileptogenic zone using High-Frequency oscillations from SEEG: A Real-World approach.

INTRODUCTION: Localizing the epileptogenic zone (EZ) using Stereo EEG (SEEG) is often challenging th...

Machine learning models and classification algorithms in the diagnosis of vestibular migraine: A systematic review and meta-analysis.

OBJECTIVES: To perform a systematic review and meta-analysis to evaluate the effectiveness of machin...

Enhancing parkinson disease detection through feature based deep learning with autoencoders and neural networks.

Parkinson's disease is a neurodegenerative disorder that is associated with aging, leading to the pr...

Compliance Evaluation with ChatGPT for Diagnosis and Treatment in Patients Brought to the ED with a Preliminary Diagnosis of Stroke.

OBJECTIVES: Chat Generative Pre-trained Transformer (ChatGPT) is a natural language processing produ...

Dual-pathway EEG model with channel attention for virtual reality motion sickness detection.

BACKGROUND: Motion sickness has been a key factor affecting user experience in Virtual Reality (VR) ...

SSAT-Swin: Deep Learning-Based Spinal Ultrasound Feature Segmentation for Scoliosis Using Self-Supervised Swin Transformer.

OBJECTIVE: Scoliosis, a 3-D spinal deformity, requires early detection and intervention. Ultrasound ...

FPGA implementation of a complete digital spiking silicon neuron for circuit design and network approach.

When attempting to replicate the same biological spiking neuron model actions of the human brain, th...

Augmenting rehabilitation robotics with spinal cord neuromodulation: A proof of concept.

Rehabilitation robotics aims to promote activity-dependent reorganization of the nervous system. How...

Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.

BACKGROUND: Early prediction of progression in dementia is of major importance for providing patient...

Neuronal and therapeutic perspectives on empathic pain: A rational insight.

Empathy is the capacity to experience and understand the feelings of others, thereby playing a key r...

A Novel Explainable Attention-Based Meta-Learning Framework for Imbalanced Brain Stroke Prediction.

The accurate prediction of brain stroke is critical for effective diagnosis and management, yet the ...

A comprehensive interpretable machine learning framework for mild cognitive impairment and Alzheimer's disease diagnosis.

An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cogn...

Non-Face-to-Face Services in Neurologic Care.

Neurologists in ambulatory settings struggle with low appointment availability and increased work re...

Dementia Overdiagnosis in Younger, Higher Educated Individuals Based on MMSE Alone: Analysis Using Deep Learning Technology.

BACKGROUND: Dementia is a multifaceted disorder that affects cognitive function, necessitating accur...

An intelligent multi-attribute decision-making system for clinical assessment of spinal cord disorder using fuzzy hypersoft rough approximations.

The data for diagnosing spinal cord disorder (SCD) are complex and often confusing, making it diffic...

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