Detecting Shape-based Interactions among Environmental Chemicals using an Ensemble of Exposure-Mixture Regression and Interpretable Machine Learning Tools
Abstract:There is growing interest in discovering interactions between multiple environmental chemicals associated with increased adverse health effects. However, most existing approaches (1) either use a projection or product of multiple chemical exposures, which are difficult to interpret, and (2) can not simultaneously handle multi-ordered interactions. Therefore, we develop and validate a method to discover shape-based interactions that mimic usual toxicological interactions. We developed the "Multi-ordered explana… Show more
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