Automated seizure detection systems face significant challenges due to the limited availability of clinical EEG data, a substantial class imbalance between seizure and non-seizure recordings, considerable variability among patients, and the issue of ...
Epileptic spasm (ES), characterized by sudden muscle contractions and loss of consciousness, poses significant challenges in early diagnosis and treatment, especially in infants and young children. Despite advances in EEG-based seizure detection, the...
The current gold standard for detecting epileptic seizures is in-hospital video-Electroencephalography (vEEG), but vEEG is resource-intensive and imposes considerable burdens on patients and caregivers. Wearable devices offer an alternative to monito...
Automated electroencephalography (EEG)-based epilepsy diagnosis has reported near-perfect accuracies for almost two decades on a benchmark dataset, yet virtually no system is used in routine care. We critically re-examined this translation gap by rep...
Epilepsy affects around 50 million people globally, causing significant burdens. While many methods predict seizures, current models struggle with handling spatiotemporal features and balancing accuracy with computational efficiency.This paper introd...
The longitudinal course of epilepsy remains largely unpredictable. This study aimed to predict final outcome and classify dynamic longitudinal trajectories using artificial intelligence. A total of 2586 patients who first visited our epilepsy special...
The brain condition known as epilepsy has an impact on patients' quality of life. The need for computer-automated diagnosis systems (CADS) has arisen due to the shortcomings of conventional clinical and machine learning techniques as well as the shor...
BACKGROUND: Epilepsy affects approximately 50 million people globally and imposes a substantial clinical and societal burden, requiring continuous and personalized monitoring for effective management. Wearable artificial intelligence (AI) technologie...
BACKGROUND AND OBJECTIVES: Epilepsy is a common neurologic disorder. Although antiseizure medications (ASMs) are the first-line treatment, identifying the most effective ASM for each individual remains a trial-and-error process. Genetic variation may...
Sleep-wake states bidirectionally interact with epilepsy and seizures, but the mechanisms are unknown. A barrier to comprehensive characterization and the study of mechanisms has been the difficulty of annotating large chronic recording datasets. To ...
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