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Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e26590b2b9ea4a1ea518c1f7f616c0c0

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach

About this item

Full title

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach

Publisher

Canada: Journal of Medical Internet Research

Journal title

Journal of medical Internet research, 2022-04, Vol.24 (4), p.e29982

Language

English

Formats

Publication information

Publisher

Canada: Journal of Medical Internet Research

More information

Scope and Contents

Contents

Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compared it with that of the conventional...

Alternative Titles

Full title

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_e26590b2b9ea4a1ea518c1f7f616c0c0

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e26590b2b9ea4a1ea518c1f7f616c0c0

Other Identifiers

ISSN

1438-8871,1439-4456

E-ISSN

1438-8871

DOI

10.2196/29982

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