Neurology

Seizures

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

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Sleep Staging Foundation Models Encode Neural Disorder-Related EEG Representations that Generalize to Wakefulness

To leverage sleep foundation models trained on large datasets of polysomnography for neurological di...

Research on Epilepsy Detection and Recognition Based on the Combination of Time Frequency Transform and Deep Learning Model

To improve the detection performance of epileptic electroencephalogram (EEG) signals and address the...

Explainable machine learning on weighted connectivity networks across frequencies for outcome prediction in comatose patients

Accurate early prediction of neurological outcomes in comatose patients after cardiac arrest is crit...

Sleep-Derived Features From Multi-Night In-ear EEG Identify Patterns Linked To Mild Cognitive Impairment

We investigated whether sleep features from multi-night, at-home in-ear EEG could distinguish mild c...

Resting-state EEG and machine learning to investigate cortical connectivity as a biomarker in chronic mTBI

Mild traumatic brain injury (mTBI) is a heterogeneous condition with long-term sequelae, yet diagnos...

Information Leakage and Performance Overestimation in EEG-Based Schizophrenia Detection: Evidence from Literature and Empirical Analyses

Detecting schizophrenia (SZ) from electroencephalography (EEG) signals using machine- and deep learn...

DeepCRI: Real-time EEG-based Prognostication after Cardiac Arrest

Accurate prediction of neurological outcome after cardiac arrest is essential for guiding intensive ...

A Comparison of Two Deep Learning Approaches to Distinguish Functional Dissociative from Epileptic Seizures Using Event Videos

Differentiating between motor functional dissociative seizures (FDS) and motor epileptic seizures (E...

Brain natural frequencies as physiologically meaningful biomarkers for machine-learning detection of Parkinson’s disease

In this study, we investigated whether individual brain maps of natural frequencies derived from EEG...

Multiscale-Multistage Temporal Convolutional Network for EEG-Based Mild Cognitive Impairment Detection

Mild cognitive impairment (MCI) is an intermediate stage between normal ageing and dementia, with af...

Is it possible to vaccinate AI against bias? An exploratory study in epilepsy

Large language models are increasingly used for clinical decision support yet may perpetuate socioec...

Surface EEG to identify cognitive motor dissociation after acute brain injury

Cognitive motor dissociation (CMD) is associated with long-term recovery in acute brain injury, but ...

Identifying EEG biomarkers of sense of embodiment in virtual reality: insights from spatio-spectral features.

The Sense of Embodiment (SoE) refers to the subjective experience of perceiving a non-biological bod...

Jan 2025 40420994
Research on emotion recognition using sparse EEG channels and cross-subject modeling based on CNN-KAN-[Formula: see text] model.

Emotion recognition plays a significant role in artificial intelligence and human-computer interacti...

Jan 2025 40424242
Smart Seizure Detection System: Machine Learning Based Model in Healthcare IoT.

BACKGROUND: Epilepsy, the tendency to have recurrent seizures, can have various causes, including br...

Jan 2025 38706349
ML-based Models as a Strategy to Discover Novel Antiepileptic Drugs Targeting Sodium Receptor Channel.

BACKGROUND: Epilepsy remains the most common and chronic disorder demanding longterm management. The...

Jan 2025 39440735
Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons.

Closed-loop electricalstimulation of brain structures is one of the most promising techniques to sup...

Jan 2025 40031444
A Systematic Review of Machine Learning Methods for Multimodal EEG Data in Clinical Application

Machine learning (ML) and deep learning (DL) techniques have been widely applied to analyze electr...

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