Explainable artificial intelligence for predicting hospital-acquired pressure injuries in covid-19–positive critical care patients

Jenny Alderden; Susan M. Kennerly; Andrew Wilson; Jonathan Dimas; Casey McFarland; David Y. Yap; Lucy Zhao; Tracey L. Yap

doi:10.1097/CIN.0000000000000943

Explainable artificial intelligence for predicting hospital-acquired pressure injuries in covid-19–positive critical care patients

Jenny Alderden, Susan M. Kennerly, Andrew Wilson, Jonathan Dimas, Casey McFarland, David Y. Yap, Lucy Zhao, Tracey L. Yap

School of Nursing

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

8 Scopus citations

Original language	English
Pages (from-to)	659-665
Number of pages	7
Journal	CIN - Computers Informatics Nursing
Volume	40
Issue number	10
DOIs	https://doi.org/10.1097/CIN.0000000000000943
State	Published - 1 Oct 2022

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title = "Explainable artificial intelligence for predicting hospital-acquired pressure injuries in covid-19–positive critical care patients",

author = "Jenny Alderden and Kennerly, \{Susan M.\} and Andrew Wilson and Jonathan Dimas and Casey McFarland and Yap, \{David Y.\} and Lucy Zhao and Yap, \{Tracey L.\}",

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AU - Alderden, Jenny

AU - Kennerly, Susan M.

AU - Wilson, Andrew

AU - Dimas, Jonathan

AU - McFarland, Casey

AU - Yap, David Y.

AU - Zhao, Lucy

AU - Yap, Tracey L.

PY - 2022/10/1

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UR - https://www.scopus.com/pages/publications/85139571726

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VL - 40

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JO - CIN - Computers Informatics Nursing

JF - CIN - Computers Informatics Nursing

IS - 10

ER -

Explainable artificial intelligence for predicting hospital-acquired pressure injuries in covid-19–positive critical care patients

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