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Oncologist phenotypes and associations with response to a machine learning-based intervention to inc...

Oncologist phenotypes and associations with response to a machine learning-based intervention to inc...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2687677835

Oncologist phenotypes and associations with response to a machine learning-based intervention to increase advance care planning: Secondary analysis of a randomized clinical trial

About this item

Full title

Oncologist phenotypes and associations with response to a machine learning-based intervention to increase advance care planning: Secondary analysis of a randomized clinical trial

Publisher

United States: Public Library of Science

Journal title

PloS one, 2022-05, Vol.17 (5), p.e0267012-e0267012

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

While health systems have implemented multifaceted interventions to improve physician and patient communication in serious illnesses such as cancer, clinicians vary in their response to these initiatives. In this secondary analysis of a randomized trial, we identified phenotypes of oncology clinicians based on practice pattern and demographic data,...

Alternative Titles

Full title

Oncologist phenotypes and associations with response to a machine learning-based intervention to increase advance care planning: Secondary analysis of a randomized clinical trial

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_2687677835

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2687677835

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0267012

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