Applications of machine learning in health management among the elderly:a scope review
ZHANG Yu
ZHOU Xu
CHEN Dan
ZHANG Yun
Abstract：Objective: To conduct a scoping review of the application of machine learning in elderly health management, providing guidance for research in this field. Methods: Based on the methodological framework of the Joanna Briggs Institute scoping review guidelines, relevant studies on the application of machine learning in elderly health management were retrieved from PubMed, EMbase, Web of Science, Scopus, CNKI, Wanfang Database, and China Biomedical Literature Database, with the search period ranging from the establishment of the databases to January 16, 2023. Data extraction and summary analysis were performed on the included literature. Results: A total of 27 articles were included, covering topics such as health risk assessment, health monitoring, and health cost management. The algorithm types included decision tree algorithms (DT), naive Bayes algorithms (NBM), support vector machine algorithms (SVM), neural network algorithms (NN), K-Means algorithms (KM), and reinforcement learning (RL). Conclusion: Machine learning is effective in health monitoring and risk warning in elderly health management. Future research should continue to focus on the practical application and effectiveness of machine learning in the field of elderly health, as well as issues related to digital security and ethics.
Keywords：machine learningartificial intelligenceelderlyhealth managementnursingscope review
Publication Date：2025-01-14
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 49-60 )