Health status prediction for the elderly based on machine learning

被引:16
作者
Qin, Fang-Yu [1 ]
Lv, Zhe-Qi [2 ]
Wang, Dan-Ni [3 ]
Hu, Bo [4 ]
Wu, Chao [3 ,5 ]
机构
[1] Zhejiang Univ, Dept Software Engn, Hangzhou, Peoples R China
[2] Zhejiang Univ, Dept Marine Informat, Hangzhou, Peoples R China
[3] Zhejiang Univ, Dept Publ Affairs, Hangzhou, Peoples R China
[4] London Sch Econ & Polit Sci, Care Policy & Evaluat Ctr, Dept Hlth Policy, London, England
[5] Zhejiang Univ, Ctr Social Welf & Governance, Hangzhou, Peoples R China
基金
浙江省自然科学基金; 中国国家自然科学基金;
关键词
Machine learning; Elderly; Health prediction; Social service; Data-driven; SELF-RATED HEALTH; DISABILITY; SUPPORT;
D O I
10.1016/j.archger.2020.104121
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Health and social care services are crucial to old people. The provision of services to the elderly with care needs requires more accurate predictions of the health status of the elderly to rationalize the allocation of the limited social care resources. The traditional analytical methods have proved incapable of predicting the demands of today's society, compared to which machine learning methods can more accurately capture the nonlinear relationships between the variables. To ascertain visually the performance of these machine learning methods regarding the prediction of the elderly's care needs, we designed and verified the experiment.
引用
收藏
页数:7
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