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Neurology Subcategories: Autism Dementia Head Trauma Parkinson's Disease Seizures Sleep Disorders

Showing 883-903 of 3,743 articles

A Transferable Deep Learning Prognosis Model for Predicting Stroke Patients' Recovery in Different Rehabilitation Trainings.

Since the underlying mechanisms of neurorehabilitation are not fully understood, the prognosis of st...

Dec 2022 PMID: 36083954

A Systematic Review of Virtual Reality and Robot Therapy as Recent Rehabilitation Technologies Using EEG-Brain-Computer Interface Based on Movement-Related Cortical Potentials.

To enhance the treatment of motor function impairment, patients' brain signals for self-control as a...

Dec 2022 PMID: 36551100

A comparison between robot-guided and stereotactic frame-based stereoelectroencephalography (SEEG) electrode implantation for drug-resistant epilepsy.

The original stereoelectroencephalography frame-based implantation technique has been proven to be s...

Dec 2022 PMID: 36454433

Epileptic Seizure Detection Using a Hybrid 1D CNN-Machine Learning Approach from EEG Data.

Electroencephalography (EEG) is a widely used technique for the detection of epileptic seizures. It ...

Nov 2022 PMID: 36483658

Automatic seizure detection by convolutional neural networks with computational complexity analysis.

BACKGROUND AND OBJECTIVES: Nowadays, an automated computer-aided diagnosis (CAD) is an approach that...

Nov 2022 PMID: 36463672

Sleep Staging Framework with Physiologically Harmonized Sub-Networks.

Sleep screening is an important tool for both healthcare and neuroscientific research. Automatic sle...

Nov 2022 PMID: 36436760

Staging study of single-channel sleep EEG signals based on data augmentation.

INTRODUCTION: Accurate sleep staging is an essential basis for sleep quality assessment and plays an...

Nov 2022 PMID: 36504972

Real-time noise cancellation with deep learning.

Biological measurements are often contaminated with large amounts of non-stationary noise which requ...

Nov 2022 PMID: 36409690

NeuroGrasp: Real-Time EEG Classification of High-Level Motor Imagery Tasks Using a Dual-Stage Deep Learning Framework.

Brain-computer interfaces (BCIs) have been widely employed to identify and estimate a user's intenti...

Nov 2022 PMID: 34748509

Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning.

BACKGROUND: The electroencephalography (EEG) signal carries important information about the electric...

Nov 2022 PMID: 36397034

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task.

Virtual reality surgical simulators have facilitated surgical education by providing a safe training...

Nov 2022 PMID: 36502696

Novel 3D video action recognition deep learning approach for near real time epileptic seizure classification.

Seizure semiology is a well-established method to classify epileptic seizure types, but requires a s...

Nov 2022 PMID: 36379994

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records.

Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of...

Nov 2022 PMID: 36371527

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy.

The present study investigates the effectiveness of a deep learning neural network for non-invasivel...

Nov 2022 PMID: 35925854

3DCANN: A Spatio-Temporal Convolution Attention Neural Network for EEG Emotion Recognition.

Since electroencephalogram (EEG) signals can truly reflect human emotional state, emotion recognitio...

Nov 2022 PMID: 34033551

Emotion recognition while applying cosmetic cream using deep learning from EEG data; cross-subject analysis.

We report a deep learning-based emotion recognition method using EEG data collected while applying c...

Nov 2022 PMID: 36355917

Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks.

BACKGROUND: Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 mill...

Nov 2022 PMID: 36352381

Neurology

Browse Specialties

A Transferable Deep Learning Prognosis Model for Predicting Stroke Patients' Recovery in Different Rehabilitation Trainings.

A Systematic Review of Virtual Reality and Robot Therapy as Recent Rehabilitation Technologies Using EEG-Brain-Computer Interface Based on Movement-Related Cortical Potentials.

A comparison between robot-guided and stereotactic frame-based stereoelectroencephalography (SEEG) electrode implantation for drug-resistant epilepsy.

Epileptic Seizure Detection Using a Hybrid 1D CNN-Machine Learning Approach from EEG Data.

Automatic seizure detection by convolutional neural networks with computational complexity analysis.

Sleep Staging Framework with Physiologically Harmonized Sub-Networks.

Staging study of single-channel sleep EEG signals based on data augmentation.

Real-time noise cancellation with deep learning.

NeuroGrasp: Real-Time EEG Classification of High-Level Motor Imagery Tasks Using a Dual-Stage Deep Learning Framework.

Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning.

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task.

Novel 3D video action recognition deep learning approach for near real time epileptic seizure classification.

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records.

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy.

3DCANN: A Spatio-Temporal Convolution Attention Neural Network for EEG Emotion Recognition.

Emotion recognition while applying cosmetic cream using deep learning from EEG data; cross-subject analysis.

Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks.

The Deep Learning Method Differentiates Patients with Bipolar Disorder from Controls with High Accuracy Using EEG Data.

M1M2: Deep-Learning-Based Real-Time Emotion Recognition from Neural Activity.

Being watched by a humanoid robot and a human: Effects on affect-related psychophysiological responses.

A review of critical challenges in MI-BCI: From conventional to deep learning methods.

Browse Specialties