Automatic prediction of obstructive sleep apnea event using deep learning algorithm based on ECG and thoracic movement signals-Reference-Cited by-同舟云学术

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Automatic prediction of obstructive sleep apnea event using deep learning algorithm based on ECG and thoracic movement signals

Published:2024-01-02 Issue:1 Volume:144 Page:52-57
ISSN:0001-6489
Container-title:Acta Oto-Laryngologica
language:en
Short-container-title:Acta Oto-Laryngologica

Author:

Li Zufei¹²,Jia Yajie¹²,Li Yanru¹²,Han Demin¹²^ORCID

Affiliation:

1. Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China

2. Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, People’s Republic of China

Funder

Beijing Municipal Administration of Hospitals’ Youth Programme

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00016489.2024.2301732

Reference18 articles.

1. A contemporary review of obstructive sleep apnea

2. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis

3. Prevalence of obstructive sleep apnea in the general population: A systematic review

4. AASM Scoring Manual Updates for 2017 (Version 2.4)

5. Prediction of obstructive sleep apnea using ensemble of recurrence plot convolutional neural networks (RPCNNs) from polysomnography signals

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