Machine Learning–Based Prediction Model Construction for Type 2 Diabetes Mellitus: A Comparison of Algorithms and Multilevel Risk Factor Analysis

Machine learning models integrating multidimensional risk factors based on the health ecology framework can more accurately predict T2DM risk, providing a scientific basis for multilevel interventions. The innovation of this study lies in the first integration of the health ecology model with machine learning technology to systematically identify cross-level risk factors. Compared with traditional models, it is more comprehensive, breaks through the limitations of previous studies, and provides a new and effective tool for the precise prevention of T2DM and public health interventions.