Micro-Macro ML Framework for Childhood Obesity Prediction
Published:Dec 28, 2025 03:20
•1 min read
•ArXiv
Analysis
This paper addresses a significant public health issue (childhood obesity) by integrating diverse datasets (NHANES, USDA, EPA) and employing a multi-level machine learning approach. The framework's ability to identify environment-driven disparities and its potential for causal modeling and intervention planning are key contributions. The use of XGBoost and the creation of an environmental vulnerability index are notable aspects of the methodology.
Key Takeaways
Reference
“XGBoost achieved the strongest performance.”