Brief digital sleep questionnaire powered by machine learning prediction models identifies common sleep disorders

AR Schwartz, M Cohen-Zion, LV Pham, A Gal… - Sleep Medicine, 2020 - Elsevier
Introduction We developed and validated an abbreviated Digital Sleep Questionnaire (DSQ)
to identify common societal sleep disturbances including insomnia, delayed sleep phase …

Diagnosis of obstructive sleep apnea in children based on the XGBoost algorithm using nocturnal heart rate and blood oxygen feature

P Ye, H Qin, X Zhan, Z Wang, C Liu, B Song… - American Journal of …, 2023 - Elsevier
Purpose Obstructive sleep apnea (OSA) is a serious type of obstructive sleep-disordered
breathing (SDB) that can cause a series of adverse effects on children's cardiovascular …

[HTML][HTML] Network science meets respiratory medicine for OSAS phenotyping and severity prediction

S Mihaicuta, M Udrescu, A Topirceanu, L Udrescu - PeerJ, 2017 - peerj.com
Obstructive sleep apnea syndrome (OSAS) is a common clinical condition. The way that
OSAS risk factors associate and converge is not a random process. As such, defining OSAS …

0537 incident hypertension prediction in obstructive sleep apnea using machine learning

OH Milani, T Nguyen, A Parekh, AE Cetin, B Prasad - Sleep, 2023 - academic.oup.com
Introduction Obstructive sleep apnea (OSA) is associated with hypertension due to
intermittent hypoxia and sleep fragmentation. Due to the complex pathogenesis of …

Screening for obstructive sleep apnea: comparing the American Academy of Sleep Medicine proposed criteria with the STOP-Bang, NoSAS, and GOAL instruments

RLM Duarte, FJ Magalhães-da-Silveira… - Journal of Clinical Sleep …, 2023 - jcsm.aasm.org
Study Objectives: We evaluated the performance of the 2017 American Academy of Sleep
Medicine criteria (AASM2017) in screening obstructive sleep apnea (OSA) and compared …

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 …

Convolutional neural network for screening of obstructive sleep apnea using snoring sounds

R Li, W Li, K Yue, Y Li - Biomedical Signal Processing and Control, 2023 - Elsevier
Screening and assessment for obstructive sleep apnea hypopnea syndrome (OSAHS) has
attracted growing attention to improve the life of patients with sleep apnea. The gold …

Cloud algorithm-driven oximetry-based diagnosis of obstructive sleep apnoea in symptomatic habitually snoring children

Z Xu, GC Gutiérrez-Tobal, Y Wu… - European …, 2019 - Eur Respiratory Soc
The ability of a cloud-driven Bluetooth oximetry-based algorithm to diagnose obstructive
sleep apnoea syndrome (OSAS) was examined in habitually snoring children concurrently …

Sleep apnea phenotyping and relationship to disease in a large clinical biobank

BE Cade, SM Hassan, HS Dashti, M Kiernan… - Jamia …, 2022 - academic.oup.com
Objective Sleep apnea is associated with a broad range of pathophysiology. While
electronic health record (EHR) information has the potential for revealing relationships …

[HTML][HTML] Age-integrated artificial intelligence framework for sleep stage classification and obstructive sleep apnea screening

C Kang, S An, HJ Kim, M Devi, A Cho… - Frontiers in …, 2023 - frontiersin.org
Introduction Sleep is an essential function to sustain a healthy life, and sleep dysfunction
can cause various physical and mental issues. In particular, obstructive sleep apnea (OSA) …