Computer scientists and mathematicians at the CEU Cardenal Herrera University in Valencia have developed a prediction model that can warn epileptic sufferers of an upcoming seizure with 20 minutes ...

Epilepsy is one of the most common neurological diseases in the world, afflicting more than 50 million people. While most forms can be treated with therapeutics, patients with drug-resistant epilepsy ...

Empatica’s Embrace device, pictured here, earned an FDA clearance in 2018 to help detect seizures, and its other AI-powered wearables have been used as predictive tools before. (Empatica) After ...

(Nasdaq: CBLL) (“Ceribell”), a medical technology company focused on transforming the diagnosis and management of patients with serious neurological conditions, today announced that a new research ...

Computer scientists and mathematicians have developed a prediction model that can warn epileptic sufferers of an upcoming seizure with 20 minutes notice. Computer scientists and mathematicians at the ...

Researchers from the Indian Institute of Technology – Delhi have come up with a novel algorithm that can localise the epileptogenic zone using a patient's EEG data. In cases of drug-resistant ...

Background and Aim: Since there is compelling evidence that seizures are harmful to the immature developing brain, accurate seizure detection at the cotside is imperative. Multichannel EEG is a ...

Two years ago, the American Epilepsy Society raised the Seizure Prevention Challenge to 502 research teams around the globe. The goal was to design a method to help epileptic patients accurately ...

A study by University of Melbourne researchers reveals clinically relevant epileptic seizure prediction is possible in a wider range of patients than previously thought, thanks to the crowdsourcing of ...

Predictions for identifying 1-year seizure recurrence performed significantly better in electroencephalography (EEG) without interictal epileptiform discharges. An automated processing algorithm ...

A study reveals clinically relevant epileptic seizure prediction is possible in a wider range of patients than previously thought, thanks to the crowdsourcing of more than 10,000 algorithms worldwide.