Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy
The diagnosis of sleep disorders such as narcolepsy and insomnia currently requires experts to interpret sleep recordings (polysomnography). Here, the authors introduce a neural network analysis method for polysomnography that could reduce time spent in sleep clinics and automate narcolepsy diagnosi...
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Nature Portfolio
2018
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oai:doaj.org-article:41bccb5b13f7400780258cc22467964a2021-12-02T15:34:40ZNeural network analysis of sleep stages enables efficient diagnosis of narcolepsy10.1038/s41467-018-07229-32041-1723https://doaj.org/article/41bccb5b13f7400780258cc22467964a2018-12-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-07229-3https://doaj.org/toc/2041-1723The diagnosis of sleep disorders such as narcolepsy and insomnia currently requires experts to interpret sleep recordings (polysomnography). Here, the authors introduce a neural network analysis method for polysomnography that could reduce time spent in sleep clinics and automate narcolepsy diagnosis.Jens B. StephansenAlexander N. OlesenMads OlsenAditya AmbatiEileen B. LearyHyatt E. MooreOscar CarrilloLing LinFang HanHan YanYun L. SunYves DauvilliersSabine ScholzLucie BarateauBirgit HoglAmbra StefaniSeung Chul HongTae Won KimFabio PizzaGiuseppe PlazziStefano VandiElena AntelmiDimitri PerrinSamuel T. KunaPaula K. SchweitzerClete KushidaPaul E. PeppardHelge B. D. SorensenPoul JennumEmmanuel MignotNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-15 (2018) |
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Science Q Jens B. Stephansen Alexander N. Olesen Mads Olsen Aditya Ambati Eileen B. Leary Hyatt E. Moore Oscar Carrillo Ling Lin Fang Han Han Yan Yun L. Sun Yves Dauvilliers Sabine Scholz Lucie Barateau Birgit Hogl Ambra Stefani Seung Chul Hong Tae Won Kim Fabio Pizza Giuseppe Plazzi Stefano Vandi Elena Antelmi Dimitri Perrin Samuel T. Kuna Paula K. Schweitzer Clete Kushida Paul E. Peppard Helge B. D. Sorensen Poul Jennum Emmanuel Mignot Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
description |
The diagnosis of sleep disorders such as narcolepsy and insomnia currently requires experts to interpret sleep recordings (polysomnography). Here, the authors introduce a neural network analysis method for polysomnography that could reduce time spent in sleep clinics and automate narcolepsy diagnosis. |
format |
article |
author |
Jens B. Stephansen Alexander N. Olesen Mads Olsen Aditya Ambati Eileen B. Leary Hyatt E. Moore Oscar Carrillo Ling Lin Fang Han Han Yan Yun L. Sun Yves Dauvilliers Sabine Scholz Lucie Barateau Birgit Hogl Ambra Stefani Seung Chul Hong Tae Won Kim Fabio Pizza Giuseppe Plazzi Stefano Vandi Elena Antelmi Dimitri Perrin Samuel T. Kuna Paula K. Schweitzer Clete Kushida Paul E. Peppard Helge B. D. Sorensen Poul Jennum Emmanuel Mignot |
author_facet |
Jens B. Stephansen Alexander N. Olesen Mads Olsen Aditya Ambati Eileen B. Leary Hyatt E. Moore Oscar Carrillo Ling Lin Fang Han Han Yan Yun L. Sun Yves Dauvilliers Sabine Scholz Lucie Barateau Birgit Hogl Ambra Stefani Seung Chul Hong Tae Won Kim Fabio Pizza Giuseppe Plazzi Stefano Vandi Elena Antelmi Dimitri Perrin Samuel T. Kuna Paula K. Schweitzer Clete Kushida Paul E. Peppard Helge B. D. Sorensen Poul Jennum Emmanuel Mignot |
author_sort |
Jens B. Stephansen |
title |
Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
title_short |
Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
title_full |
Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
title_fullStr |
Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
title_full_unstemmed |
Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
title_sort |
neural network analysis of sleep stages enables efficient diagnosis of narcolepsy |
publisher |
Nature Portfolio |
publishDate |
2018 |
url |
https://doaj.org/article/41bccb5b13f7400780258cc22467964a |
work_keys_str_mv |
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