Prediction Model of Elderly Care Willingness Based on Machine Learning

At present, the problem of an aging population in China is severe. The integration existing healthcare services with elderly care inefficient and cannot meet needs elderly. As such, urgently concerted efforts various social forces to cope increasingly serious aging. In accordance Andersen’s behavioral model, a survey was conducted Tangshan City among seniors 60 years age older. Using logistic regression models, decision tree random forest we examined factors impacting senior people’s desire choose integrated medical nursing model. results three models displayed that elderly’s propensity combined model significantly influenced by amount insurance, life needs, needs. Moreover, study found willingness improve service system low. government should appeal community participate multiple developments system.