Abstract Purpose of Review Machine Learning (ML) and Artificial Intelligence (AI) are data-
driven techniques to translate raw data into applicable and interpretable insights that can …

Brain interictal epileptiform discharges (IEDs), as one of the hallmarks of epileptic brain, are
transient events captured by electroencephalogram (EEG). IEDs are generated by seizure …

Epilepsy as the most common neurological disorder globally has drawn more and more
attention. However, it is time-consuming and labor-intensive for manual detection of interictal …

Objective Deep learning methods have shown potential in automating the detection of
interictal epileptiform discharges (IEDs) in electroencephalography (EEG). We compared …

Epilepsy is one of the most serious nervous system diseases; it can be diagnosed accurately
by video electroencephalogram. In this study, we analyzed microstate epileptic …

Objective Interictal epileptiform discharges (IED) are hallmark biomarkers of epilepsy which
are typically detected through visual analysis. Deep learning has shown potential in …

As the main component of Brain-computer interface (BCI) technology, the classification
algorithm based on EEG has developed rapidly. The previous algorithms were often based …

Objective. Electroencephalogram (EEG) analysis has always been an important tool in
neural engineering, and the recognition and classification of human emotions are one of the …

Objective: This study develops new machine learning architectures that are more adept at
detecting interictal epileptiform discharges (IEDs) in scalp EEG. A comparison of results …

Epilepsy is a group of brain disorders characterised by an enduring predisposition to
generate unprovoked seizures. Fuelled by advances in sequencing technologies and …