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 …

Background Obstructive sleep apnea (OSA) is a globally prevalent disease with a complex
diagnostic method. Severe OSA is associated with multi-system dysfunction. We aimed to …

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 …

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 …

Study objectives Obstructive sleep apnea (OSA) is a major concern in modern medicine;
however, it is difficult to diagnose. Screening questionnaires such as the Berlin …

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

Abstract Study Objectives Polysomnography is the gold standard for diagnosis of obstructive
sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to …

To develop an applicable prediction for obstructive sleep apnea (OSA) is still a challenge in
clinical practice. We apply a modern machine learning method, the support vector machine …

This study aimed to investigate the applicability of machine learning to predict obstructive
sleep apnea (OSA) among individuals with suspected OSA in South Korea. A total of 92 …

Background American Academy of Sleep Medicine guidelines suggest that clinical
prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) …