Neurology

Seizures

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

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Brain Oscillations in Bipolar Disorder: Insights from Quantitative EEG Studies.

IntroductionQuantitative electroencephalography (QEEG) is a neurophysiological tool that analyzes br...

Investigating Membership Inference Attacks against CNN Models for BCI Systems.

As Deep Learning (DL) algorithms become more widely adopted in healthcare applications, there is a g...

Evaluating the impact of an AI-powered chatbot on epilepsy education and stigma reduction: A pre-post intervention study using EpiloBot.

OBJECTIVE: Effective epilepsy management requires accurate epilepsy knowledge, active patient engage...

Wavelet-Attention deep model for pediatric ADHD diagnosis via EEG.

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in childr...

Electrical stimulation of stem cell-derived human neural networks for evaluating anti-seizure medications.

OBJECTIVE: Current preclinical epilepsy drug screening relies on animal models that poorly reflect h...

Application of machine learning in EEG-based dementia diagnosis: Classification and differential diagnosis.

BackgroundElectroencephalogram (EEG) is a promising, non-invasive method for identifying the presenc...

EEG-based speech imagery decoding by dynamic hypergraph learning within projected and selected feature subspaces.

Speech imagery is a nascent paradigm that is receiving widespread attention in current brain-compute...

Predicting delirium in critically Ill COVID-19 patients using EEG-derived data: a machine learning approach.

Delirium is a severe and common complication among critically ill patients, particularly those with ...

Harnessing electroencephalography connectomes for cognitive and clinical neuroscience.

Electroencephalography (EEG) connectomes offer powerful tools for studying brain connectivity and ad...

Joint Fine-Grained Representation Learning and Masked Relational Modeling for EEG-Based Automatic Sleep Staging in Fabric Space.

Sleep staging is a crucial method for the evaluation of sleep quality and the diagnosis of sleep dis...

Enhanced Online Continuous Brain-Control by Deep Learning-based EEG Decoding.

OBJECTIVE: A growing amount of deep learning models for motor imagery (MI) decoding from electroence...

Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device.

Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, ...

Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks.

Accurate and efficient analysis of Electroencephalogram (EEG) signals is crucial for applications li...

EEG microstate analysis in children with prolonged disorders of consciousness.

Prolonged disorders of consciousness (pDoC) in children lack objective and effective diagnostic meth...

M4CEA: A Knowledge-guided Foundation Model for Childhood Epilepsy Analysis.

Existing electroencephalogram (EEG)-based deep learning models are mainly designed for single or sev...

Prediction of Epilepsy Seizure Based on Cepstrum Analysis and Deep Learning.

There are specific changes in the frequency components of the electroencephalogram (EEG) signals bef...

Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.

Timely detection of cognitive decline is paramount for effective intervention, prompting researchers...

DAFF-SNN: Dual Attention-driven and Feature Fusion-based Spiking Neural Network for Epilepsy Detection based on Electroencephalogram.

Electroencephalogram (EEG) signals provide rich spatiotemporal brain features crucial for epilepsy d...

Comparative effectiveness of anti-seizure medications in emulated trials using medical informatics.

Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar...

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