Latest AI and machine learning research in seizures for healthcare professionals.
Information Retrieval (IR) systems primarily rely on users' ability to translate their internal in...
Intracranial EEG (iEEG) recording, characterized by high spatial and temporal resolution and super...
Electroencephalogram (EEG) signals play a pivotal role in biomedical research and clinical applica...
Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in...
This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) di...
Electroencephalogram (EEG) brain networks describe the driving and synchronous relationships among m...
Epilepsy is known to drastically alter brain dynamics during seizures (ictal periods), but its eff...
Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic ...
Electroencephalogram (EEG)-based seizure subtype classification enhances clinical diagnosis effici...
A brain-computer interface (BCI) enables direct communication between the brain and an external de...
In this paper, we propose a conceptual framework for personalized brain-computer interface (BCI) a...
Attention is a vital cognitive process in the learning and memory environment, particularly in the...
This study investigates the sleep characteristics and brain activity of individuals in the gray zo...
Sleep staging is a crucial task in sleep monitoring and diagnosis, but clinical sleep staging is bot...
Analyzing electroencephalogram (EEG) signals to detect the epileptic seizure status of a subject p...
Neural biomarkers that can classify or predict disease are of broad interest to the neurological a...
Introduction Schizophrenia is a severe mental disorder, and early diagnosis is key to improving ou...
Importance: Many individuals with drug-resistant epilepsy continue to have seizures after resectiv...
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) introdu...
Understanding the correlation between EEG features and cognitive tasks is crucial for elucidating ...