Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients

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
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/f84bcc357880499c918c1874c4e4b670
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https://doaj.org/article/f84bcc357880499c918c1874c4e4b670

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