Objectives: The goal of this study is to evaluate the results of machine learning methods for
the classification of OSA severity of patients with suspected sleep disorder breathing as …

Objectives: To evaluate the role of clinical scores assessing the risk of disease severity in
patients with clinical suspicion of obstructive sleep apnea syndrome (OSA). The hypothesis …

Introduction: Obstructive sleep apnea syndrome has become an important public health
concern. Polysomnography is traditionally considered an established and effective …

As the incidence of obstructive sleep apnea syndrome (OSAS) increases worldwide, the
need for a new screening method that can compensate for the shortcomings of the …

Background: The currently available polysomnography (PSG) equipments and operating
personnel are facing increasing pressure, such situation may result in the problem that a …

Study Objectives: Home sleep apnea testing (HSAT) is an efficient and cost-effective method
of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates …

Our study's main purpose is to emphasise the significance of medical knowledge of
pathophysiology before machine learning. We investigated whether combining domain …

Background The high cost and low availability of polysomnography (PSG) limits the timely
diagnosis of OSA. Herein, we developed and validated a simple-to-use nomogram for …

Obstructive sleep apnea (OSA) is a widespread disorder that is cumbersome to diagnose
using the goldstandard, overnight polysomnography (PSG). This paper highlights further …

Obstructive sleep apnea (OSA) is a common, chronic, sleep-related breathing disorder
characterized by partial or complete airway obstruction in sleep. The gold standard …