Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy
have increased exponentially over the past decade. Integration of AI into epilepsy …

Epilepsy is a highly prevalent chronic neurological disorder with great negative impact on
patients' daily lives. Despite this there is still no adequate technological support to enable …

The need for high-quality automated seizure detection algorithms based on
electroencephalography (EEG) becomes ever more pressing with the increasing use of …

Epilepsy is a chronic neurological disorder that affects a significant portion of the human
population and imposes serious risks in the daily life. Despite advances in machine learning …

Epilepsy is a life-threatening neurological condition. Manual detection of epileptic seizures
(ES) is laborious and burdensome. Machine learning techniques applied to …

Introduction Long-term electroencephalography (EEG) monitoring is advised to patients with
refractory epilepsy who have a failure of anti-seizure medication and therapy. However, its …

Epilepsy is a chronic neurological disorder with a significant prevalence. However, there is
still no adequate technological support to enable epilepsy detection and continuous …

This study presents a novel approach for EEG-based seizure detection leveraging a BERT-
based model. The model, BENDR, undergoes a two-phase training process. Initially, it is pre …

Hyperdimensional (HD) computing is a novel approach to machine learning inspired by
neuroscience, which uses vectors in a hyper-dimensional space to represent data and …

Epilepsy is a neurological disorder characterized by abnormal electrical activity of the brain
that causes recurrent seizures. Electroencephalography (EEG) data can help in the …