Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy

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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Auteurs principaux: 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
Format: article
Langue:EN
Publié: Nature Portfolio 2018
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Accès en ligne:https://doaj.org/article/41bccb5b13f7400780258cc22467964a
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https://doaj.org/article/41bccb5b13f7400780258cc22467964a

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