Deep Learning for Diagnosis and Classification of Obstructive Sleep Apnea: A Nasal Airflow-Based Multi-Resolution Residual Network

PURPOSE: This study evaluated a novel approach for diagnosis and classification of obstructive sleep apnea (OSA), called Obstructive Sleep Apnea Smart System (OSASS), using residual networks and single-channel nasal pressure airflow signals. METHODS: Data were collected from the sleep center of the...

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Detalles Bibliográficos
Autores principales: Yue, Huijun, Lin, Yu, Wu, Yitao, Wang, Yongquan, Li, Yun, Guo, Xueqin, Huang, Ying, Wen, Weiping, Zhao, Gansen, Pang, Xiongwen, Lei, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966385/
https://www.ncbi.nlm.nih.gov/pubmed/33737850
http://dx.doi.org/10.2147/NSS.S297856

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966385/
https://www.ncbi.nlm.nih.gov/pubmed/33737850
http://dx.doi.org/10.2147/NSS.S297856

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