Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40040010
Interictal epileptiform discharges (IEDs) are electrophysiological events that intermittently occur in between seizures in Epilepsy patients. Automated detection of IEDs is crucial for assisting clinicians in epilepsy diagnosis as they can help ident...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039835
450,000 children with epilepsy in the United States suffer lifelong disability and are at risk of sudden death. Surgical treatment of epilepsy is limited by the ability to visually discriminate between normal and abnormal brain tissue using visual li...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039682
Interictal epileptic discharge (IED) detection from electroencephalography (EEG) is an important but difficult step in the epilepsy diagnosis. To reduce the workload of doctors, some diagnostic auxiliary methods based on deep learning have been propo...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039673
Graph neural networks show strong capability of learning spatial relationships between channels. In recent studies, they greatly advanced automatic epileptic seizures detection via multi-channels scalp electroencephalography (EEG). In this work, we u...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039604
Epilepsy, traditionally conceptualized as a neurological disorder characterized by a persistent inclination toward epileptic seizures, is commonly diagnosed and monitored through EEGs. However, manual analysis of EEG data can be exceedingly time-cons...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039571
Epilepsy is a disease of the brain that causes unprovoked or reflex seizures that affects millions of individuals worldwide. Traditionally, identifying epileptic states involves assessing neuroimaging scans or brain electrical signals recorded by EEG...
In the field of clinical neurology, automated detection of epileptic seizures based on electroencephalogram (EEG) signals has the potential to significantly accelerate the diagnosis of epilepsy. This rapid and accurate diagnosis enables doctors to pr...
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
40086096
INTRODUCTION: Localizing the epileptogenic zone (EZ) using Stereo EEG (SEEG) is often challenging through manual analysis. Even methods based on signal analysis have limitations in identifying the EZ, particularly in patients with neocortical epileps...
AIMS: Artificial intelligence (AI) tools like ChatGPT hold promise for enhancing diagnostic accuracy and efficiency in clinical practice. This exploratory study evaluates ChatGPT's performance in diagnosing and classifying epileptic seizures, epileps...
Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EE...