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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Detalles Bibliográficos
Autores principales: Rodriguez-Morilla, Beatriz, Estivill, Eduard, Estivill-Domènech, Carla, Albares, Javier, Segarra, Francisco, Correa, Angel, Campos, Manuel, Rol, Maria Angeles, Madrid, Juan Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916421/
https://www.ncbi.nlm.nih.gov/pubmed/31920488
http://dx.doi.org/10.3389/fnins.2019.01318

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916421/
https://www.ncbi.nlm.nih.gov/pubmed/31920488
http://dx.doi.org/10.3389/fnins.2019.01318

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