With the increase in biosensors and data collection devices in the healthcare industry,
artificial intelligence and machine learning have attracted much attention in recent years. In …

Sleep staging is an essential step in the diagnosis and treatment of sleep-related diseases.
Currently, most supervised learning models face the problem of insufficient labeled data. In …

Despite the progress recently made towards automatic sleep staging for adults, children
have complicated sleep structures that require attention to the pediatric sleep staging. Semi …

Objective Most seizure forecasting algorithms have relied on features specific to
electroencephalographic recordings. Environmental and physiological factors, such as …

Background While the effects of prolonged sleep deprivation (≥ 24 h) on seizure
occurrence has been thoroughly explored, little is known about the effects of day-to-day …

Automated text categorization methods are of broad relevance for domain experts since they
free researchers and practitioners from manual labeling, save their resources (eg, time …

Electrical brain stimulation is a proven therapy for epilepsy, but long-term seizure free
outcomes are rare. Early implantable devices were developed for open-loop stimulation …

Introduction Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current
core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a …

Introduction Polysomnographic recordings are essential for diagnosing many sleep
disorders, yet their detailed analysis presents considerable challenges. With the rise of …

The rapid advancement of natural language processing (NLP) and machine learning (ML)
techniques, coupled with the accumulation of data and knowledge resources in the recent …