[HTML][HTML] Review of application of machine learning as a screening tool for diagnosis of obstructive sleep apnea
Obstructive sleep apnea syndrome (OSAS) is a pervasive disorder with an incidence
estimated at 5–14 percent among adults aged 30–70 years. It carries significant morbidity …
estimated at 5–14 percent among adults aged 30–70 years. It carries significant morbidity …
Diagnosis of obstructive sleep apnea using logistic regression and artificial neural networks models
Regrettably, a large proportion of likely patients with sleep apnea are underdiagnosed.
Obstructive sleep apnea (OSA) is one of the main causes of hypertension, type II diabetes …
Obstructive sleep apnea (OSA) is one of the main causes of hypertension, type II diabetes …
[HTML][HTML] Systematic Review of Detecting Sleep Apnea Using Artificial Intelligence: An Insight to Convolutional Neural Network Method
Background: Sleep apnea is a prevalent sleep disorder, especially in males and older ages.
The common diagnostic methods, including polysomnography (PSG), are expensive, difficult …
The common diagnostic methods, including polysomnography (PSG), are expensive, difficult …
[HTML][HTML] Towards validating the effectiveness of obstructive sleep apnea classification from electronic health records using machine learning
Obstructive sleep apnea (OSA) is a common, chronic, sleep-related breathing disorder
characterized by partial or complete airway obstruction in sleep. The gold standard …
characterized by partial or complete airway obstruction in sleep. The gold standard …
[HTML][HTML] Application of various machine learning techniques to predict obstructive sleep apnea syndrome severity
H Han, J Oh - Scientific Reports, 2023 - nature.com
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 …
need for a new screening method that can compensate for the shortcomings of the …
[HTML][HTML] Machine learning identification of obstructive sleep apnea severity through the patient clinical features: a retrospective study
A Maniaci, PM Riela, G Iannella, JR Lechien… - Life, 2023 - mdpi.com
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 …
patients with clinical suspicion of obstructive sleep apnea syndrome (OSA). The hypothesis …
Diagnosis of obstructive sleep apnea in patients with associated comorbidity
F Del Campo, CA Arroyo, C Zamarrón… - Advances in the Diagnosis …, 2022 - Springer
Obstructive sleep apnea (OSA) is a heterogeneous disease with many physiological
implications. OSA is associated with a great diversity of diseases, with which it shares …
implications. OSA is associated with a great diversity of diseases, with which it shares …
[HTML][HTML] Enabling early obstructive sleep apnea diagnosis with machine learning: systematic review
D Ferreira-Santos, P Amorim, T Silva Martins… - Journal of Medical …, 2022 - jmir.org
Background American Academy of Sleep Medicine guidelines suggest that clinical
prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) …
prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) …
Application of machine learning to predict obstructive sleep apnea syndrome severity
Introduction: Obstructive sleep apnea syndrome has become an important public health
concern. Polysomnography is traditionally considered an established and effective …
concern. Polysomnography is traditionally considered an established and effective …
A prediction model based on artificial neural networks for the diagnosis of obstructive sleep apnea
H Karamanli, T Yalcinoz, MA Yalcinoz, T Yalcinoz - Sleep and Breathing, 2016 - Springer
Background Recently, artificial neural networks (ANNs) have been widely applied in
science, engineering, and medicine. In the present study, we evaluated the ability of artificial …
science, engineering, and medicine. In the present study, we evaluated the ability of artificial …
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