Epileptic seizure prediction is one of the most used therapeutic adjuvant strategies for drug-
resistant epilepsy. Conventional methods usually adopt handcrafted features and manual …

Epilepsy is a neurological disorder, and clinicians usually diagnose epilepsy by interpreting
electroencephalogram (EEG) manually. This paper proposes a novel automatic epileptic …

Epileptic seizure is a neurological condition caused by short and unexpectedly occurring
electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide …

Deep learning (DL) methods have been widely used in the field of seizure prediction from
electroencephalogram (EEG) in recent years. However, DL methods usually have numerous …

Background A seizure prediction system can detect seizures prior to their occurrence and
allow clinicians to provide timely treatment for patients with epilepsy. Research on seizure …

This paper presents compact yet comprehensive feature representations for the
electroencephalogram (EEG) signal to achieve efficient epileptic seizure prediction …

Background Epilepsy is one of the most common neurological conditions globally, and the
fourth most common in the United States. Recurrent non-provoked seizures characterize it …

Electroencephalography signals obtained from the brain's electrical activity are commonly
used for the diagnosis of neurological diseases. These signals indicate the electrical activity …

Objective. This paper introduces a fully automated, subject-specific deep-learning
convolutional neural network (CNN) system for forecasting seizures using ambulatory …

Epileptic seizure detection and prediction are significantly sought-after research currently
because robust algorithms are available. Machine learning and deep learning have allowed …