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...

Full description

Saved in:

Bibliographic Details
Main Authors:	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
Language:	EN
Published:	Nature Portfolio 2018
Subjects:	Science Q
Online Access:	https://doaj.org/article/41bccb5b13f7400780258cc22467964a
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy

Similar Items