Health status prediction for the elderly based on machine learning.

Journal: Archives of gerontology and geriatrics
Published Date:

Abstract

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.

Authors

  • Fang-Yu Qin
    Department of Software Engineering, Zhejiang University, Hangzhou, China.
  • Zhe-Qi Lv
    Department of Marine Informatics, Zhejiang University, Hangzhou, China.
  • Dan-Ni Wang
    Department of Public Affairs, Zhejiang University, Hangzhou, China.
  • Bo Hu
    Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
  • Chao Wu