Neurology

Seizures

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

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Role of hippocampus in epileptogenesis: new insights in the cross-talks between the underlying mechanisms.

As a component of the limbic system, the hippocampal region, one of the deep structures of the media...

ICU-EEG Pattern Detection by a Convolutional Neural Network.

OBJECTIVE: Patients in the intensive care unit (ICU) often require continuous EEG (cEEG) monitoring ...

Unravelling the genetic complexity of drug-resistant epilepsy: a critical narrative review.

INTRODUCTION: Drug-resistant epilepsy (DRE) affects 30% of epilepsy patients and represents a major ...

Contrastive representation learning with transformers for robust auditory EEG decoding.

Decoding of continuous speech from electroencephalography (EEG) presents a promising avenue for unde...

Evaluating crowdsourcing for ICU EEG annotation: A comparison with expert performance.

OBJECTIVE: Detection of seizures and rhythmic or periodic patterns (SRPPs) on electroencephalography...

PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces.

Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative...

VR-based gamma sensory stimulation: a pilot feasibility study.

Alzheimer's disease (AD) presents a critical global health challenge, with current therapies offerin...

A computational eye state classification model using EEG signal based on data mining techniques: comparative analysis.

Artificial Intelligence has shown great promise in healthcare, particularly in non-invasive diagnost...

Enhancing Brain Source Reconstruction by Initializing 3D Neural Networks with Physical Inverse Solutions.

Reconstructing brain sources is a fundamental challenge in neuroscience, crucial for understanding b...

Frontiers in EEG as a tool for the management of pediatric epilepsy: Past, present, and future.

Electroencephalography (EEG) has evolved into an indispensable tool in pediatric epilepsy, fundament...

Mapping EEG-based hypnosis research: a bibliometric study.

Hypnosis, traditionally studied as a psychological phenomenon, is increasingly explored through elec...

Cross-subject EEG signals-based emotion recognition using contrastive learning.

Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant f...

Neurogenetic biomarkers in epilepsy: A comprehensive narrative review of progression and therapeutic approaches.

Epilepsy is a multifaceted and heterogenous neurological disorder that affects an estimated 70 milli...

xEEGNet: Towards explainable AI in EEG dementia classification.

OBJECTIVE: This work presents xEEGNet, a novel, compact, and explainable neural network for EEG data...

Classification accuracy of pain intensity induced by leg blood flow restriction during walking using machine learning based on electroencephalography.

Pain assessment in clinical practice largely relies on patient-reported subjectivity. Although previ...

AI-Driven Electrographic Seizure Classification and Seizure Onset Detection Using Image- and Time-Series-Based Approaches.

OBJECTIVE: Manually distinguishing between seizure and non-seizure events in intracranial electroenc...

Interpretable Cross-Modal Alignment Network for EEG Visual Decoding With Algorithm Unrolling.

Accurate decoding in electroencephalography (EEG) technology, particularly for rapid visual stimuli,...

Radiomics, machine learning, and deep learning for hippocampal sclerosis identification: a systematic review and diagnostic meta-analysis.

PURPOSE: Hippocampal sclerosis (HS) is the primary pathological finding in temporal lobe epilepsy (T...

Association between long-term exposure of polystyrene microplastics and exacerbation of seizure symptoms: Evidence from multiple approaches.

Microplastics are tiny plastic particles originating from both commercial product manufacturing and ...

Enhancing EEG-Based Schizophrenia Diagnosis with Explainable Multi-Branch Deep Learning.

Schizophrenia poses diagnostic challenges due to a lack of objective assessment. We propose MBSzEEGN...

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