Study Objectives: Machine learning (ML) models have been employed in the setting of sleep
disorders. This review aims to summarize the existing data about the role of ML techniques …

A major challenge in big and high-dimensional data analysis is related to the classification
and prediction of the variables of interest by characterizing the relationships between the …

Study objectives This study aimed to develop a deep learning–based model to detect
obstructive sleep apnea (OSA) using craniofacial photographs. Methods Participants …

Patients with obstructive sleep apnea (OSA) show autonomic, mood, cognitive, and
breathing dysfunctions that are linked to increased morbidity and mortality, which can be …

Dramatic raising of Deep Learning (DL) approach and its capability in biomedical
applications lead us to explore the advantages of using DL for sleep Apnea-Hypopnea …

Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is
characterized by partial or complete obstruction of the upper airway during sleep. The …

The most appropriate physiological signals to develop simplified as well as accurate
screening tests for obstructive sleep apnoea (OSA) remain unknown. This study aimed at …

Background Sleep apnea (OSA) is a common sleep disorder characterized by recurring
breathing pauses during sleep caused by a blockage of the upper airway (UA). The altered …

Sleep apnea is a common disorder that can cause pauses in breathing and can last from a
few seconds to several minutes, as well as shallow breathing or complete cessation of …

Many wearables allow physiological data acquisition in sleep and enable clinicians to
assess sleep outside of sleep labs. Belun Sleep Platform (BSP) is a novel neural network …