We instead propose that improved feature selection alongside collaboration, data standardization, and model sharing is required to advance the field.
SUDEP
Featuring the work of former CURE Epilepsy grantee Dr. Edward Glasscock.
A study that could lead to the identification of biomarkers to help identify people at risk for sudden unexpected death in epilepsy (SUDEP).
Weaning was associated with increased seizures and behavioral disturbances in a subset. An approach targeting potassium channel dysfunction with ezogabine is warranted in patients with KCNQ2-related DEE.
This study provides insight into the perspectives of users and offers recommendations for implementing automated spike and seizure detection in EMUs.
Socioeconomic hardship (increased neighborhood disadvantage) exerts a significant adverse impact on the cognitive and academic status of youth with new and recent onset epilepsies, an impact that needs to be incorporated into etiological models of the neurobehavioral comorbidities of epilepsy.
Many state-of-the-art methods for seizure prediction, using the electroencephalogram, are based on machine learning models that are black boxes, weakening the trust of clinicians in them for high-risk decisions.
If we can avoid patients not progressing to the need for IV anesthesia, intubation and an ICU stay that can sometimes be prolonged, that’s going to be lifesaving.
Genetics, Pediatric Epilepsy
The latest research on cannabidiol and seizures, the possible cause of infantile and epileptic spasms syndrome, the brain's immune system, and more in this issue of Epilepsy Research News.
Wearable automated detection devices of focal epileptic seizures are needed to alert patients and caregivers and to optimize the medical treatment. Heart rate variability (HRV)-based seizure detection devices have presented good detection sensitivity. However, false alarm rates (FAR) are too high.
