Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19-Positive Critical Care Patients.

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

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

Alderden J; Author Affiliations: University of Utah College of Nursing, Salt Lake City (Drs Alderden, Dimas, and McFarland); East Carolina University School of Nursing, Greenville, NC (Dr Kennerly); Real World Data Analytics, Parexel International, Durham, NC, and University of Utah College of Nursing (Dr Wilson); Boise State University School of Nursing, ID (Dr Zhao); and Duke University School of Nursing, Durham, NC (Dr Yap).

Comput Inform Nurs ; 40(10): 659-665, 2022 Oct 01.

Article in English | MEDLINE | ID: covidwho-2063016

Subject(s)

COVID-19; Pressure Ulcer; Artificial Intelligence; Critical Care; Hospitals; Humans; Pressure Ulcer/epidemiology

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pressure Ulcer / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Comput Inform Nurs Journal subject: Nursing / Medical Informatics Year: 2022 Document Type: Article

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