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Application of a Decision Tree Model to Predict the Outcome of Non-Intensive Inpatients Hospitalized...

Application of a Decision Tree Model to Predict the Outcome of Non-Intensive Inpatients Hospitalized...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9602523

Application of a Decision Tree Model to Predict the Outcome of Non-Intensive Inpatients Hospitalized for COVID-19

About this item

Full title

Application of a Decision Tree Model to Predict the Outcome of Non-Intensive Inpatients Hospitalized for COVID-19

Publisher

Switzerland: MDPI AG

Journal title

International journal of environmental research and public health, 2022-10, Vol.19 (20), p.13016

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Many studies have identified predictors of outcomes for inpatients with coronavirus disease 2019 (COVID-19), especially in intensive care units. However, most retrospective studies applied regression methods to evaluate the risk of death or worsening health. Recently, new studies have based their conclusions on retrospective studies by applying mac...

Alternative Titles

Full title

Application of a Decision Tree Model to Predict the Outcome of Non-Intensive Inpatients Hospitalized for COVID-19

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9602523

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9602523

Other Identifiers

ISSN

1660-4601,1661-7827

E-ISSN

1660-4601

DOI

10.3390/ijerph192013016

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