Neurology

Seizures

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

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Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework.

Although increasing evidences support the notion that psychiatric disorders are associated with abno...

A Hybrid Expert System for Individualized Quantification of Electrical Status Epilepticus During Sleep Using Biogeography-Based Optimization.

Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with co...

A multi-modal assessment of sleep stages using adaptive Fourier decomposition and machine learning.

Healthy sleep is essential for the rejuvenation of the body and helps in maintaining good health. Ma...

EEG based depression recognition using improved graph convolutional neural network.

Depression is a global psychological disease that does serious harm to people. Traditional diagnosti...

Granger Causality Inference in EEG Source Connectivity Analysis: A State-Space Approach.

This article addresses the problem of estimating brain effective connectivity from electroencephalog...

Spatio-Spectral Feature Representation for Motor Imagery Classification Using Convolutional Neural Networks.

Convolutional neural networks (CNNs) have recently been applied to electroencephalogram (EEG)-based ...

EEGSym: Overcoming Inter-Subject Variability in Motor Imagery Based BCIs With Deep Learning.

In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI) based Brain C...

Cross-Platform Implementation of an SSVEP-Based BCI for the Control of a 6-DOF Robotic Arm.

Robotics has been successfully applied in the design of collaborative robots for assistance to peopl...

A Multimodal AI System for Out-of-Distribution Generalization of Seizure Identification.

Artificial intelligence (AI) and health sensory data-fusion hold the potential to automate many labo...

SEEG-Net: An explainable and deep learning-based cross-subject pathological activity detection method for drug-resistant epilepsy.

OBJECTIVE: Precise preoperative evaluation of drug-resistant epilepsy (DRE) requires accurate analys...

A method for AI assisted human interpretation of neonatal EEG.

The study proposes a novel method to empower healthcare professionals to interact and leverage AI de...

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load.

Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; ...

Drowsiness Detection Using Ocular Indices from EEG Signal.

Drowsiness is one of the main causes of road accidents and endangers the lives of road users. Recent...

EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review.

Epileptic seizure is one of the most chronic neurological diseases that instantaneously disrupts the...

A novel deep learning model based on the ICA and Riemannian manifold for EEG-based emotion recognition.

BACKGROUND: The EEG-based emotion recognition is one of the primary research orientations in the fie...

The Masking Impact of Intra-Artifacts in EEG on Deep Learning-Based Sleep Staging Systems: A Comparative Study.

Elimination of intra-artifacts in EEG has been overlooked in most of the existing sleep staging syst...

HDI Highlighter, The First Intelligent Tool to Screen the Literature on Herb-Drug Interactions.

Herbal food supplements are commonly used and can be an important part of patient self-care. Like al...

Symmetric Convolutional and Adversarial Neural Network Enables Improved Mental Stress Classification From EEG.

Electroencephalography (EEG) is widely used for mental stress classification, but effective feature ...

Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb func...

A Data-Driven Adaptive Emotion Recognition Model for College Students Using an Improved Multifeature Deep Neural Network Technology.

With the increasing pressure on college students in terms of study, work, emotion, and life, the emo...

A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

The classification of sleep stages is an important process. However, this process is time-consuming,...

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