Automated multi-model deep neural network for sleep stage scoring with unfiltered clinical data

PURPOSE: To develop an automated framework for sleep stage scoring from PSG via a deep neural network. METHODS: An automated deep neural network was proposed by using a multi-model integration strategy with multiple signal channels as input. All of the data were collected from one single medical cen...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaoqing, Xu, Mingkai, Li, Yanru, Su, Minmin, Xu, Ziyao, Wang, Chunyan, Kang, Dan, Li, Hongguang, Mu, Xin, Ding, Xiu, Xu, Wen, Wang, Xingjun, Han, Demin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Sleep Breathing Physiology and Disorders • Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289784/
https://www.ncbi.nlm.nih.gov/pubmed/31938990
http://dx.doi.org/10.1007/s11325-019-02008-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289784/
https://www.ncbi.nlm.nih.gov/pubmed/31938990
http://dx.doi.org/10.1007/s11325-019-02008-w

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