Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy

Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage sco...

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Detalles Bibliográficos
Autores principales: Stephansen, Jens B., Olesen, Alexander N., Olsen, Mads, Ambati, Aditya, Leary, Eileen B., Moore, Hyatt E., Carrillo, Oscar, Lin, Ling, Han, Fang, Yan, Han, Sun, Yun L., Dauvilliers, Yves, Scholz, Sabine, Barateau, Lucie, Hogl, Birgit, Stefani, Ambra, Hong, Seung Chul, Kim, Tae Won, Pizza, Fabio, Plazzi, Giuseppe, Vandi, Stefano, Antelmi, Elena, Perrin, Dimitri, Kuna, Samuel T., Schweitzer, Paula K., Kushida, Clete, Peppard, Paul E., Sorensen, Helge B. D., Jennum, Poul, Mignot, Emmanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283836/
https://www.ncbi.nlm.nih.gov/pubmed/30523329
http://dx.doi.org/10.1038/s41467-018-07229-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283836/
https://www.ncbi.nlm.nih.gov/pubmed/30523329
http://dx.doi.org/10.1038/s41467-018-07229-3

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