A machine learning algorithm-based predictive model for pressure injury risk in emergency patients: A prospective cohort study.

Journal: International emergency nursing

Published Date: Mar 2, 2024

Abstract

OBJECTIVES: To construct pressure injury risk prediction models for emergency patients based on different machine learning algorithms, to optimize the best model, and to provide a suitable assessment tool for preventing the occurrence of pressure injuries in emergency patients.

Authors

Li Wei

The First Affiliate Hospital of Guangzhou Medical University, Guangzhou, China.
Honglei Lv

Tianjin Medical University General Hospital, Tianjin, China.
Chenqi Yue

Tianjin Medical University General Hospital, Tianjin, China.
Ying Yao

Tianjin Medical University General Hospital, Tianjin, China.
Ning Gao

Department of Chemistry & Biochemistry, University of Texas at El Paso, Texas, USA.
Qianwen Chai

Tianjin Medical University General Hospital Airport Site, Tianjin, China.
Minghui Lu

Tianjin Medical University General Hospital Airport Site, Tianjin, China.

Keywords

Adult Aged Algorithms China Cohort Studies Decision Trees Emergency Service, Hospital Female Humans Incidence Logistic Models Machine Learning Male Middle Aged Pressure Ulcer Prospective Studies Risk Assessment Risk Factors

External Resources

View on PubMed Access via DOI PubMed (38432045)

A machine learning algorithm-based predictive model for pressure injury risk in emergency patients: A prospective cohort study.

Abstract

Authors

Keywords

External Resources

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