A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data

Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity and mortality in COPD patients. Apart from patients with obvious EI, the identification of a such behavior during a real-life consultation is unreliable. We therefore describe a machine learning algorit...

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Detalles Bibliográficos
Autores principales: Aguilaniu, Bernard, Hess, David, Kelkel, Eric, Briault, Amandine, Destors, Marie, Boutros, Jacques, Zhi Li, Pei, Antoniadis, Anestis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376055/
https://www.ncbi.nlm.nih.gov/pubmed/34411121
http://dx.doi.org/10.1371/journal.pone.0255977

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376055/
https://www.ncbi.nlm.nih.gov/pubmed/34411121
http://dx.doi.org/10.1371/journal.pone.0255977

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