Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

ABSTRACT: This study aims to construct a prediction model for the demand for medical and daily care services of the elderly and to explore the factors that affect the demand for medical and daily care services of the elderly. In this study, a questionnaire survey on the demand for medical and daily care services of 1291 elderly was conducted using multi-stage stratified whole cluster random sampling. SPSS21.0 statistical analysis software was used to describe the basic data of the elderly statistically, and univariate analysis was used to screen variables for model construction and binary logistic regression analysis. The acquired dataset has class imbalance, and to handle this issue, Synthetic Minority Over Sampling Technique with TomekLink (SMOTE-TomekLink) was adopted to resample the dataset for

SUBMITTER: Yang G 

PROVIDER: S-EPMC11897399 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature