An online machine learning model for predicting medication adherence in hypertensive patients: data from the China health and retirement longitudinal study (CHARLS)

This study developed an XGBoost machine learning model and online tool to predict medication adherence in Chinese hypertensive patients. The tool provided immediately actionable and transparent risk stratification, enabling targeted intervention. Future research should perform external validation of the model using electronic medical records or objective adherence data, thereby enhancing its generalizability and practical utility.