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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| Auteurs principaux: | , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Public Library of Science (PLoS)
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/b351d20fc81e4d319057331ae87b6bd7 |
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