Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients-Reference-Cited by-同舟云学术

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

Published:2022-10 Issue:10 Volume:40 Page:659-665
ISSN:1538-9774
Container-title:CIN: Computers, Informatics, Nursing
language:en
Short-container-title:

Author:

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

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

Reference35 articles.

1. Risk factors for pressure injuries among critical care patients: a systematic review;International Journal of Nursing Studies,2017

2. The national cost of hospital-acquired pressure injuries in the United States;International Wound Journal,2019

3. The Braden Scale for predicting pressure sore risk;Nursing Research,1987

4. Pressure injury risk assessment in intensive care units: comparison of the reliability and predictive validity of the Braden and Jackson/Cubbin scales;Journal of Clinical Nursing,2019

5. Predictive validity of the Braden Scale for pressure injury risk assessment in adults: a systematic review and meta-analysis;Nursing Open,2021

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Explainable Artificial Intelligence for Early Prediction of Pressure Injury Risk;American Journal of Critical Care;2024-09-01

2. Identification of predictive patient characteristics for assessing the probability of COVID-19 in-hospital mortality;PLOS Digital Health;2024-04-23

3. Stressors, emotions, and social support systems among respiratory nurses during the Omicron outbreak in China: a qualitative study;BMC Nursing;2024-03-21

4. Identification of predictive patient characteristics for assessing the probability of COVID-19 in-hospital mortality;2023-07-18

5. Leveraging artificial intelligence and decision support systems in hospital-acquired pressure injuries prediction: A comprehensive review;Artificial Intelligence in Medicine;2023-07