Using casual inference and machine learning with exposure determinant modeling to identify important workplace controls

Our causal inference approach with machine learning algorithms overcomes the common limitations of exposure determinant modeling and produces easy-to-interpret estimates of biomarker concentration reductions from hypothetical workplace controls. This can aid industrial hygienists in choosing the most effective hazard controls that can be contextualized to their particular work setting.