Over the past few years, artificial intelligence (AI) has emerged as a powerful tool used to
efficiently automate several tasks across multiple domains. Sleep medicine is perfectly …

Sleep disorders, prevalent in the general population, present significant health challenges.
The current diagnostic approach, based on a manual analysis of overnight polysomnograms …

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 …

Abstract Study Objectives To quantify the amount of sleep stage ambiguity across expert
scorers and to validate a new auto-scoring platform against sleep staging performed by …

Study objectives Development of inter-database generalizable sleep staging algorithms
represents a challenge due to increased data variability across different datasets. Sharing …

Sleep disorders are symptomatic hallmarks of a variety of medical conditions. Accurately
identifying the specific stage in which these disorders occur is particularly important for the …

Since electroencephalogram (EEG) is a significant basis to treat and diagnose somnipathy,
sleep electroencephalogram automatic staging methods play important role in the treatment …

Differentiation of central disorders of hypersomnolence (DOH) is challenging but important
for patient care. This study aimed to investigate whether biomarkers derived from sleep …

Many neuro-degenerative diseases are difficult to diagnose in their early stages. For
example, early diagnosis of Mild Cognitive Impairment (MCI) requires a wide variety of tests …

Study objectives To investigate inter-scorer agreement and scoring time differences
associated with visual and computer-assisted analysis of polysomnographic (PSG) …