Application of Machine Learning Methods to Ambulatory Circadian Monitoring (ACM) for Discriminating Sleep and Circadian Disorders

The present study proposes a classification model for the differential diagnosis of primary insomnia (PI) and delayed sleep phase disorder (DSPD), applying machine learning methods to circadian parameters obtained from ambulatory circadian monitoring (ACM). Nineteen healthy controls and 242 patients...

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Dettagli Bibliografici
Pubblicato in:Front Neurosci
Autori principali: Rodriguez-Morilla, Beatriz, Estivill, Eduard, Estivill-Domènech, Carla, Albares, Javier, Segarra, Francisco, Correa, Angel, Campos, Manuel, Rol, Maria Angeles, Madrid, Juan Antonio
Natura: Artigo
Lingua:Inglês
Pubblicazione: Frontiers Media S.A. 2019
Soggetti:
Neuroscience
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6916421/
https://ncbi.nlm.nih.gov/pubmed/31920488
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2019.01318
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