Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients
Abstract The combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients through improved risk stratification and patient outcome prediction. However, in resource constrained environments the clinical utility of such...
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Auteurs principaux: | Sam Nguyen, Ryan Chan, Jose Cadena, Braden Soper, Paul Kiszka, Lucas Womack, Mark Work, Joan M. Duggan, Steven T. Haller, Jennifer A. Hanrahan, David J. Kennedy, Deepa Mukundan, Priyadip Ray |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/f84bcc357880499c918c1874c4e4b670 |
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