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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Tallennettuna:
Bibliografiset tiedot
Julkaisussa:Front Neurosci
Päätekijät: Rodriguez-Morilla, Beatriz, Estivill, Eduard, Estivill-Domènech, Carla, Albares, Javier, Segarra, Francisco, Correa, Angel, Campos, Manuel, Rol, Maria Angeles, Madrid, Juan Antonio
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Frontiers Media S.A. 2019
Aiheet:
Neuroscience
Linkit: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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