Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients with Head and Neck Cancer

David Forner

doi:10.1001/jamaoto.2022.1629

Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients with Head and Neck Cancer

David Forner

Physics and Astronomy

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Original language	English
Pages (from-to)	764-772
Number of pages	9
Journal	JAMA Otolaryngology - Head and Neck Surgery
Volume	148
Issue number	8
DOIs	https://doi.org/10.1001/jamaoto.2022.1629
Publication status	Published - Aug 2022

ASJC Scopus Subject Areas

Surgery
Otorhinolaryngology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1001/jamaoto.2022.1629

Cite this

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Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients with Head and Neck Cancer

ASJC Scopus Subject Areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Reports Outline Head and Neck Cancer Study Results from University of Toronto (Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients With Head and Neck Cancer)

Cite this

Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients with Head and Neck Cancer

ASJC Scopus Subject Areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Press/Media

Reports Outline Head and Neck Cancer Study Results from University of Toronto (Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients With Head and Neck Cancer)

Cite this