A machine learning-based test for adult sleep apnoea screening at home using oximetry and airflow

The most appropriate physiological signals to develop simplified as well as accurate screening tests for obstructive sleep apnoea (OSA) remain unknown. This study aimed at assessing whether joint analysis of at-home oximetry and airflow recordings by means of machine-learning algorithms leads to a s...

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Detalles Bibliográficos
Autores principales: Álvarez, Daniel, Cerezo-Hernández, Ana, Crespo, Andrea, Gutiérrez-Tobal, Gonzalo C., Vaquerizo-Villar, Fernando, Barroso-García, Verónica, Moreno, Fernando, Arroyo, C. Ainhoa, Ruiz, Tomás, Hornero, Roberto, del Campo, Félix
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093547/
https://www.ncbi.nlm.nih.gov/pubmed/32210294
http://dx.doi.org/10.1038/s41598-020-62223-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093547/
https://www.ncbi.nlm.nih.gov/pubmed/32210294
http://dx.doi.org/10.1038/s41598-020-62223-4

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