Neurology

Seizures

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

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DCSENets: Interpretable deep learning for patient-independent seizure classification using enhanced EEG-based spectrogram visualization.

Neurologists often face challenges in identifying epileptic activities within multichannel EEG recor...

Neuropathology of focal epilepsy: the promise of artificial intelligence and digital Neuropathology 3.0.

Focal lesions of the human neocortex often cause drug-resistant epilepsy, yet ​surgical resection of...

Enhancing Deep-Learning Classification for Remote Motor Imagery Rehabilitation Using Multi-Subject Transfer Learning in IoT Environment.

One of the most promising applications for electroencephalogram (EEG)-based brain-computer interface...

Annotated interictal discharges in intracranial EEG sleep data and related machine learning detection scheme.

Interictal epileptiform discharges (IEDs) such as spikes and sharp waves represent pathological elec...

Monitoring of the trough concentration of valproic acid in pediatric epilepsy patients: a machine learning-based ensemble model.

AIMS: Few personalized monitoring models for valproic acid (VPA) in pediatric epilepsy patients (PEP...

EEG channel and feature investigation in binary and multiple motor imagery task predictions.

INTRODUCTION: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic...

Identification of autism spectrum disorder using electroencephalography and machine learning: a review.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by communication barr...

Detecting fast-ripples on both micro- and macro-electrodes in epilepsy: A wavelet-based CNN detector.

BACKGROUND: Fast-ripples (FR) are short (∼10 ms) high-frequency oscillations (HFO) between 200 and 6...

How accurate are machine learning models in predicting anti-seizure medication responses: A systematic review.

IMPORTANCE: Current epilepsy management protocols often depend on anti-seizure medication (ASM) tria...

Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG analysis using machine learning.

OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are prevalent neurodegenerativ...

Enhancing motor imagery EEG signal decoding through machine learning: A systematic review of recent progress.

This systematic literature review explores the intersection of neuroscience and deep learning in the...

A novel ECG-based approach for classifying psychiatric disorders: Leveraging wavelet scattering networks.

Individuals with neuropsychiatric disorders experience both physical and mental difficulties, hinder...

Humanity Test-EEG Data Mediated Artificial Intelligence Multi-Person Interactive System.

Artificial intelligence (AI) systems are widely applied in various industries and everyday life, par...

Unlocking Security for Comprehensive Electroencephalogram-Based User Authentication Systems.

With recent significant advancements in artificial intelligence, the necessity for more reliable rec...

Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis.

BACKGROUND: Real-time monitoring of pediatric epileptic seizures poses a significant challenge in cl...

Digital Twin for EEG seizure prediction using time reassigned Multisynchrosqueezing transform-based CNN-BiLSTM-Attention mechanism model.

The prediction of epileptic seizures is a classical research problem, representing one of the most c...

Enhancing automatic sleep stage classification with cerebellar EEG and machine learning techniques.

Sleep disorders have become a significant health concern in modern society. To investigate and diagn...

3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal.

Non-invasive brain-computer interfaces (BCI) hold great promise in the field of neurorehabilitation....

TdCCA with Dual-Modal Signal Fusion: Degenerated Occipital and Frontal Connectivity of Adult Moyamoya Disease for Early Identification.

Cognitive impairment in patients with moyamoya disease (MMD) manifests earlier than clinical symptom...

Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer's Disease Detection via Amplitude Transformation.

This study investigates the effectiveness of amplitude transformation in enhancing the performance a...

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