학술논문
Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy
Document Type
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
Source
Nature Communications, Vol 9, Iss 1, Pp 1-15 (2018)
Subject
Language
English
ISSN
2041-1723
Abstract
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.