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

Showing 736-756 of 3,743 articles

A fine-tuning deep residual convolutional neural network for emotion recognition based on frequency-channel matrices representation of one-dimensional electroencephalography.

Emotion recognition (ER) plays a crucial role in enabling machines to perceive human emotional and p...

Nov 2023 PMID: 38017703

ADHD/CD-NET: automated EEG-based characterization of ADHD and CD using explainable deep neural network technique.

UNLABELLED: In this study, attention deficit hyperactivity disorder (ADHD), a childhood neurodevelop...

Nov 2023 PMID: 39104684

Study on brain damage patterns of COVID-19 patients based on EEG signals.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused...

Nov 2023 PMID: 38077190

Assessing the performance of ChatGPT's responses to questions related to epilepsy: A cross-sectional study on natural language processing and medical information retrieval.

BACKGROUND: Epilepsy is a neurological condition marked by frequent seizures and various cognitive a...

Nov 2023 PMID: 38007922

An Effective Hybrid Deep Learning Model for Single-Channel EEG-Based Subject-Independent Drowsiness Recognition.

Nowadays, road accidents pose a severe risk in cases of sleep disorders. We proposed a novel hybrid ...

Nov 2023 PMID: 37995000

Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network.

Interpretation of neural activity in response to stimulations received from the surrounding environm...

Nov 2023 PMID: 38067727

Combining brain-computer interfaces with deep reinforcement learning for robot training: a feasibility study in a simulation environment.

Deep reinforcement learning (RL) is used as a strategy to teach robot agents how to autonomously lea...

Nov 2023 PMID: 38234482

EESCN: A novel spiking neural network method for EEG-based emotion recognition.

BACKGROUND AND OBJECTIVE: Although existing artificial neural networks have achieved good results in...

Nov 2023 PMID: 38000320

Oscillatory Responses to Tactile Stimuli of Different Intensity.

Tactile perception encompasses several submodalities that are realized with distinct sensory subsyst...

Nov 2023 PMID: 38005672

Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.

Recently, convolutional neural network (CNN)-based classification models have shown good performance...

Nov 2023 PMID: 37934650

An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection.

To avoid traffic accidents, monitoring the driver's electroencephalogram (EEG) signals to assess dro...

Nov 2023 PMID: 37964570

Performance evaluation of metaheuristics-tuned recurrent neural networks for electroencephalography anomaly detection.

Electroencephalography (EEG) serves as a diagnostic technique for measuring brain waves and brain ac...

Nov 2023 PMID: 38033337

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is prim...

Nov 2023 PMID: 37963517

Space-CNN: a decision classification method based on EEG signals from different brain regions.

Decision-making plays a critical role in an individual's interpersonal interactions and cognitive pr...

Nov 2023 PMID: 37953335

Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network.

Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It...

Nov 2023 PMID: 38005443

Hybrid optimization assisted channel selection of EEG for deep learning model-based classification of motor imagery task.

OBJECTIVES: To design and develop an approach named HC + SMA-SSA scheme for classifying motor imager...

Nov 2023 PMID: 37935217

Illuminating the Neural Landscape of Pilot Mental States: A Convolutional Neural Network Approach with Shapley Additive Explanations Interpretability.

Predicting pilots' mental states is a critical challenge in aviation safety and performance, with el...

Nov 2023 PMID: 38005440

Neurology

Browse Specialties

A fine-tuning deep residual convolutional neural network for emotion recognition based on frequency-channel matrices representation of one-dimensional electroencephalography.

ADHD/CD-NET: automated EEG-based characterization of ADHD and CD using explainable deep neural network technique.

Study on brain damage patterns of COVID-19 patients based on EEG signals.

Assessing the performance of ChatGPT's responses to questions related to epilepsy: A cross-sectional study on natural language processing and medical information retrieval.

An Effective Hybrid Deep Learning Model for Single-Channel EEG-Based Subject-Independent Drowsiness Recognition.

Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network.

Combining brain-computer interfaces with deep reinforcement learning for robot training: a feasibility study in a simulation environment.

EESCN: A novel spiking neural network method for EEG-based emotion recognition.

Oscillatory Responses to Tactile Stimuli of Different Intensity.

Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.

An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection.

Performance evaluation of metaheuristics-tuned recurrent neural networks for electroencephalography anomaly detection.

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

Space-CNN: a decision classification method based on EEG signals from different brain regions.

Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network.

Hybrid optimization assisted channel selection of EEG for deep learning model-based classification of motor imagery task.

Illuminating the Neural Landscape of Pilot Mental States: A Convolutional Neural Network Approach with Shapley Additive Explanations Interpretability.

IMH-Net: a convolutional neural network for end-to-end EEG motor imagery classification.

Aided diagnosis of cervical spondylotic myelopathy using deep learning methods based on electroencephalography.

A deep learning-based approach for distinguishing different stress levels of human brain using EEG and pulse rate.

ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data.

Browse Specialties