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Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simula...

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simula...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2572891953

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study

About this item

Full title

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study

Publisher

United States: Public Library of Science

Journal title

PloS one, 2021-09, Vol.16 (9), p.e0257005

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.
Using simulated data, we use a ML algorithmic framework to evaluate data imputation performance and the resul...

Alternative Titles

Full title

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_2572891953

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2572891953

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0257005

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