Machine learning approaches to predict hip fracture incidence: insights from the CHARLS dataset

The machine learning-based predictive model developed in this study demonstrated strong predictive performance for incident hip fractures over a 7-year period. By incorporating readily available, modifiable lifestyle factors, the model serves as a promising tool for identifying individuals at high risk. It provides a scientific basis for developing early intervention strategies, but requires further prospective validation before clinical implementation.