Machine Learning May Improve Seizure Prediction in Epilepsy
Researchers studied how machine learning (ML) can help predict where seizures start in patients with drug-resistant epilepsy (DRE).
Researchers studied how machine learning (ML) can help predict where seizures start in patients with drug-resistant epilepsy (DRE).
Researchers studied three cases of infantile epilepsy, which is a type of epilepsy that affects babies from birth to two years old.
Researchers studied how pediatric hospitals in Canada use imaging methods, like MRI and CT scans, to evaluate children who have new-onset seizures.
A study was conducted to look at how effective Vagus Nerve Stimulation (VNS) is for children with drug-resistant epilepsy (DRE), which means their seizures do not respond well to medication.
This study looked at how people with epilepsy manage their own medications.
This study looked at different methods used to create consensus-based recommendations (CBRs) for epilepsy care.
This study looked at how Finnish adolescents with epilepsy transition to adult healthcare.
Researchers studied how certain brain activities change as children grow into adolescents and young adults, focusing on people with epilepsy aged 3 to 33 years.
Researchers studied how to better locate epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC), a condition that can cause epilepsy.