Machine learning models in hospice care:a scope review
10.3761/j.issn.0254-1769.2025.12.019
- VernacularTitle:机器学习模型在安宁疗护中应用的范围综述
- Author:
Chunjian XU
1
;
Tingting CAI
;
Yifei XIE
;
Aiyong ZHU
;
Lijuan SONG
Author Information
1. 201203 上海市 上海中医药大学研究生院
- Publication Type:Journal Article
- Keywords:
Hospice Care;
Machine Learning;
Scoping Review;
Nursing Care
- From:
Chinese Journal of Nursing
2025;60(12):1524-1531
- CountryChina
- Language:Chinese
-
Abstract:
Objective To systematically search the research literature related to the application of machine learning models in hospice care,with a view to providing references for clinical practice.Methods A systematic search of Wanfang database,CNKI,VIP database,China Biomedical Literature Database,PubMed,Embase,Scopus,Cochrane Library,Web of Science,and CINAHL was conducted in accordance with the methodology of the scoping review as a guideline,with the timeframe of searching from the establishment of the database to August 30,2024,and the included literature was screened,summarized,extracted,and analyzed.Results Totally 17 studies were included.Analysis revealed that supervised machine learning algorithms(including random forest,decision tree,and neural networks)predominated in palliative care applications.Data sources and collection methods varied widely,with models applied across diverse scenarios.Model functions include assessing hospice needs,predicting a patient's risk of death,assisting with symptom management,analyzing hospice communication content,and more.Conclusion Machine learning models in palliative care demonstrate considerable utility and broad applicability.Future research should enhance data quality,optimize model development workflows,and improve model performance.
