Predicting Community-Onset Candidemia in an Academic Medical Center Using Machine Learning

Predicting Community-Onset Candidemia in an Academic Medical Center Using Machine Learning

Background: Candidemia is a leading cause of bloodstream infections (BSIs), and community-onset candidemia is being recognized as a public health problem. In the era of electronic health records (EHRs), we can use machine learning to detect patterns in patient data that may predict infections. Objec...

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Hlavní autoři: Mohammed Alzunitan, Alexandre R. Marra, Michael B. Edmond, Nick Street, Daniel J. Diekema, Jorge Salinas
Médium: Artigo
Jazyk:angličtina
Vydáno: 2020
On-line přístup:https://doi.org/10.1017/ice.2020.974
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/0A97E6401F9954B8F5F805105C0DE95A/S0899823X20009745a.pdf/div-class-title-predicting-community-onset-candidemia-in-an-academic-medical-center-using-machine-learning-div.pdf
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https://doi.org/10.1017/ice.2020.974
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/0A97E6401F9954B8F5F805105C0DE95A/S0899823X20009745a.pdf/div-class-title-predicting-community-onset-candidemia-in-an-academic-medical-center-using-machine-learning-div.pdf

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