Neurology

Seizures

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

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Benchmarking brain-computer interface algorithms: Riemannian approaches vs convolutional neural networks.

To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural ne...

Assessing Consciousness in Patients With Disorders of Consciousness Using a Musical Stimulation Paradigm and Verifiable Criteria.

Numerous studies have shown that musical stimulation can activate corresponding functional brain are...

An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping.

Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain ima...

Subject-independent auditory spatial attention detection based on brain topology modeling and feature distribution alignment.

Auditory spatial attention detection (ASAD) seeks to determine which speaker in a surround sound fie...

The influence of mental calculations on brain regions and heart rates.

Performing mathematical calculations is a cognitive activity that can affect biological signals. Thi...

Wasserstein generative adversarial network with gradient penalty and convolutional neural network based motor imagery EEG classification.

Due to the difficulty in acquiring motor imagery electroencephalography (MI-EEG) data and ensuring i...

Robustness of ML-Based Seizure Prediction Using Noisy EEG Data From Limited Channels.

Seizures pose a significant health hazard for over 50 million individuals with epilepsy worldwide, w...

Cochlear Implant Artifacts Removal in EEG-Based Objective Auditory Rehabilitation Assessment.

Cochlear implant (CI) is a neural prosthesis that can restore hearing for patients with severe to pr...

Joint use of population pharmacokinetics and machine learning for prediction of valproic acid plasma concentration in elderly epileptic patients.

BACKGROUND: Valproic acid (VPA) is a commonly used broad-spectrum antiepileptic drug. For elderly ep...

Detection of Pilots' Psychological Workload during Turning Phases Using EEG Characteristics.

Pilot behavior is crucial for aviation safety. This study aims to investigate the EEG characteristic...

MFCC-CNN: A patient-independent seizure prediction model.

BACKGROUND: Automatic prediction of seizures is a major goal in the field of epilepsy. However, the ...

Contrastive fine-grained domain adaptation network for EEG-based vigilance estimation.

Vigilance state is crucial for the effective performance of users in brain-computer interface (BCI) ...

An efficient channel recurrent Criss-cross attention network for epileptic seizure prediction.

Epilepsy is a chronic disease caused by repeated abnormal discharge of neurons in the brain. Accurat...

Convolutional neural networks can identify brain interactions involved in decoding spatial auditory attention.

Human listeners have the ability to direct their attention to a single speaker in a multi-talker env...

Automatically Extracting and Utilizing EEG Channel Importance Based on Graph Convolutional Network for Emotion Recognition.

Graph convolutional network (GCN) based on the brain network has been widely used for EEG emotion re...

DSFE: Decoding EEG-Based Finger Motor Imagery Using Feature-Dependent Frequency, Feature Fusion and Ensemble Learning.

Accurate decoding finger motor imagery is essential for fine motor control using EEG signals. Howeve...

DCNet: A Self-Supervised EEG Classification Framework for Improving Cognitive Computing-Enabled Smart Healthcare.

Cognitive computing endeavors to construct models that emulate brain functions, which can be explore...

Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate i...

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