Real-Time Seizure Detection for Children Using Deep Learning
Researchers studied how to detect and classify different types of seizures in children using advanced computer technology called deep learning.
Researchers studied how to detect and classify different types of seizures in children using advanced computer technology called deep learning.
This study looked at the safety and effectiveness of diazepam nasal spray for people with Rett syndrome who experience seizure clusters.
This study looked at how certain brain activity signals, called biomarkers, can help predict how well invasive treatments for drug-resistant epilepsy (DRE) work.
Researchers studied neurocysticercosis (NCC), an infection caused by the larvae of the Taenia solium parasite, which affects the brain and is a major cause of epilepsy in certain regions.
Researchers studied seizures that start in a part of the brain called the precuneus.
Researchers studied the effects of transcranial direct current stimulation (tDCS) on various psychiatric and neurological disorders, including epilepsy, major depressive disorder, schizophrenia, alcohol use disorder, stroke, and fibromyalgia.
Researchers studied the characteristics of epilepsy in patients with Muscle-Eye-Brain disease (MEB), a rare genetic condition that affects muscle and brain development.
Researchers studied genetic testing for epilepsy in families, focusing on patients who have epilepsy and at least one close relative with the condition.
This study looked at two tools used to evaluate the quality of research on epilepsy, specifically focusing on studies that examine psychiatric conditions in people with epilepsy.