Neurology

Seizures

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

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Towards Brain Passage Retrieval -- An Investigation of EEG Query Representations

Information Retrieval (IR) systems primarily rely on users' ability to translate their internal in...

A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy through Spatial Information Integration

Intracranial EEG (iEEG) recording, characterized by high spatial and temporal resolution and super...

STEAM-EEG: Spatiotemporal EEG Analysis with Markov Transfer Fields and Attentive CNNs

Electroencephalogram (EEG) signals play a pivotal role in biomedical research and clinical applica...

Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification

Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in...

An ADHD Diagnostic Interface Based on EEG Spectrograms and Deep Learning Techniques

This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) di...

Crucial rhythms and subnetworks for emotion processing extracted by an interpretable deep learning framework from EEG networks.

Electroencephalogram (EEG) brain networks describe the driving and synchronous relationships among m...

Dec 2024 39707986
Topological analysis of brain dynamical signals indicates signatures of seizure susceptibility

Epilepsy is known to drastically alter brain dynamics during seizures (ictal periods), but its eff...

Prediction of Post Traumatic Epilepsy Using MR-Based Imaging Markers.

Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic ...

Dec 2024 39560185
Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification

Electroencephalogram (EEG)-based seizure subtype classification enhances clinical diagnosis effici...

Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces

A brain-computer interface (BCI) enables direct communication between the brain and an external de...

Towards Personalized Brain-Computer Interface Application Based on Endogenous EEG Paradigms

In this paper, we propose a conceptual framework for personalized brain-computer interface (BCI) a...

A Multi-Label EEG Dataset for Mental Attention State Classification in Online Learning

Attention is a vital cognitive process in the learning and memory environment, particularly in the...

EEG Spectral Analysis in Gray Zone Between Healthy and Insomnia

This study investigates the sleep characteristics and brain activity of individuals in the gray zo...

A Feature Fusion Model Based on Temporal Convolutional Network for Automatic Sleep Staging Using Single-Channel EEG.

Sleep staging is a crucial task in sleep monitoring and diagnosis, but clinical sleep staging is bot...

Nov 2024 39504300
Real-time Sub-milliwatt Epilepsy Detection Implemented on a Spiking Neural Network Edge Inference Processor

Analyzing electroencephalogram (EEG) signals to detect the epileptic seizure status of a subject p...

The Effect of Acute Stress on the Interpretability and Generalization of Schizophrenia Predictive Machine Learning Models

Introduction Schizophrenia is a severe mental disorder, and early diagnosis is key to improving ou...

Seizure freedom after surgical resection of diffusion-weighted MRI abnormalities

Importance: Many individuals with drug-resistant epilepsy continue to have seizures after resectiv...

From Epilepsy Seizures Classification to Detection: A Deep Learning-based Approach for Raw EEG Signals

Epilepsy represents the most prevalent neurological disease in the world. One-third of people suff...

NECOMIMI: Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion Models

NECOMIMI (NEural-COgnitive MultImodal EEG-Informed Image Generation with Diffusion Models) introdu...

Feature Estimation of Global Language Processing in EEG Using Attention Maps

Understanding the correlation between EEG features and cognitive tasks is crucial for elucidating ...

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