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Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG
BACKGROUND: This paper proposes a novel method for automatically identifying sleep apnea (SA) severity based on deep learning from a short-term normal electrocardiography (ECG) signal. METHODS: A convolutional neural network (CNN) was used as an identification model and implemented using a one-dimen...
Autores principales: | Urtnasan, Erdenebayar, Park, Jong-Uk, Joo, Eun Yeon, Lee, Kyoung Joung |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Academy of Medical Sciences
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721560/ https://www.ncbi.nlm.nih.gov/pubmed/33289367 http://dx.doi.org/10.3346/jkms.2020.35.e399 |
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