Predicting hospital admission at emergency department triage using machine learning

Woo Suk Hong; Adrian Daniel Haimovich; R. Andrew Taylor

doi:10.1371/journal.pone.0201016

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Open Access

Peer-reviewed

Research Article

Predicting hospital admission at emergency department triage using machine learning

Woo Suk Hong,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Yale School of Medicine, New Haven, Connecticut, United States of America

http://orcid.org/0000-0003-3479-178X

⨯
Adrian Daniel Haimovich,

Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

Affiliation Yale School of Medicine, New Haven, Connecticut, United States of America
⨯
R. Andrew Taylor

Roles Conceptualization, Data curation, Methodology, Project administration, Resources, Supervision, Writing – review & editing

* E-mail: richard.taylor@yale.edu

Affiliation Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America

http://orcid.org/0000-0002-9082-6644

⨯

Predicting hospital admission at emergency department triage using machine learning

Woo Suk Hong,
Adrian Daniel Haimovich,
R. Andrew Taylor

Published: July 20, 2018
https://doi.org/10.1371/journal.pone.0201016

About the Authors

Woo Suk Hong

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Yale School of Medicine, New Haven, Connecticut, United States of America

http://orcid.org/0000-0003-3479-178X

Adrian Daniel Haimovich

Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

Affiliation Yale School of Medicine, New Haven, Connecticut, United States of America

R. Andrew Taylor

Roles Conceptualization, Data curation, Methodology, Project administration, Resources, Supervision, Writing – review & editing

* E-mail: richard.taylor@yale.edu

Affiliation Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America

http://orcid.org/0000-0002-9082-6644

Competing Interests

The authors have declared that no competing interests exist.

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Triage
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Critical care and emergency medicine
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Hospitals
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Forecasting
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Electronic medical records
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Outpatients
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Cardiology
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Neural networks
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