Neurology

Seizures

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

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ExSEnt for explainable dementia detection: disentangling temporal and amplitude-driven complexity boosts EEG-based classification

Early detection of dementia enables timely intervention and better care planning. Electroencephalogr...

NeuroCanvas: VLLM-Powered Robust Seizure Detection by Reformulating Multichannel EEG as Image

Accurate and timely seizure detection from Electroencephalography (EEG) is critical for clinical int...

SLIM-Diff: Shared Latent Image-Mask Diffusion with Lp loss for Data-Scarce Epilepsy FLAIR MRI

Focal cortical dysplasia (FCD) lesions in epilepsy FLAIR MRI are subtle and scarce, making joint ima...

G3DCT: An Interpretable Spatial Grid-based Framework with Temporal Convolution-Transformer for EEG Artifact Identification

Electroencephalography (EEG) serves as a fundamental tool in modern neurology, cognitive neuroscienc...

Geometry- and Relation-Aware Diffusion for EEG Super-Resolution

Recent electroencephalography (EEG) spatial super-resolution (SR) methods, while showing improved qu...

Neural Signals Generate Clinical Notes in the Wild

Generating clinical reports that summarize abnormal patterns, diagnostic findings, and clinical inte...

Assembling the Mind's Mosaic: Towards EEG Semantic Intent Decoding

Enabling natural communication through brain-computer interfaces (BCIs) remains one of the most prof...

Noninvasive and Objective Near Real-Time Detection of Pain Changes in Fluctuating Pain

Chronic pain involves natural intensity fluctuations that patients cannot control, contributing to l...

An Implantable Device that Converses with Patients and Learns to Co-Manage Epilepsy

One-third of the world's 70 million people with epilepsy have seizures that are not controlled by me...

Temporal Dynamics of EEG Decoding for Continuously Changing Visual Stimuli

Multivariate analyses of M/EEG data are typically performed on neural responses time-locked to discr...

RAICL: Retrieval-Augmented In-Context Learning for Vision-Language-Model Based EEG Seizure Detection

Electroencephalogram (EEG) decoding is a critical component of medical diagnostics, rehabilitation e...

Experience with Single Domain Generalization in Real World Medical Imaging Deployments

A desirable property of any deployed artificial intelligence is generalization across domains, i.e. ...

Time-frequency embedding with contrastive pre-training allows sub-second seizure detection

Rapid and accurate detection of electrographic seizures is critical for both clinical diagnosis and ...

EEG-Titans: Long-Horizon Seizure Forecasting via Dual-Branch Attention and Neural Memory

Accurate epileptic seizure prediction from electroencephalography (EEG) remains challenging because ...

Sleep dynamics and epileptogenesis following Kainic acid in epilepsy-susceptible (DBA/2J) and epilepsy-resistant (C57BL/6) mice

Susceptibility to epileptogenesis varies in humans and outbred mouse strains. We hypothesized that b...

ConvMambaNet: A Hybrid CNN-Mamba State Space Architecture for Accurate and Real-Time EEG Seizure Detection

Epilepsy is a chronic neurological disorder marked by recurrent seizures that can severely impact qu...

Depression Detection Based on Electroencephalography Using a Hybrid Deep Neural Network CNN-GRU and MRMR Feature Selection

This study investigates the detection and classification of depressive and non-depressive states usi...

Transformer-based EEG Source Imaging Enables Robust Localization of Pathological High-Frequency Oscillations in Epilepsy

ObjectiveHigh-frequency oscillations (HFOs) are highly specific biomarkers of epileptogenic tissue, ...

Simulation of Natural Language from Brain Activity Using Wearable EEG and Deep Learning

Severe motor impairments such as amyotrophic lateral sclerosis and locked-in syndrome lead to partia...

Leveraging Pretrained Vision Transformers for classifying Alcohol Use Disorder using Raw Resting-State EEG

Alcohol Use Disorder (AUD) is a prevalent and debilitating neuropsychiatric condition characterized ...

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