An Interpretable Machine Learning-Based Multi-Model Framework for Constructing and Characterizing a County-Level Chronic Illness Vulnerability Index
This study presents an interpretable machine learning-based multi-model framework for constructing and characterizing a county-level chronic illness vulnerability index that integrates five domains: health burden, social conditions, environmental exposure, behavioral factors, and COVID-19-related measures.