Considering how confounding impacts the association between an outcome and a predictor of interest, it is important to control for the correct variables to avoid spurious associations. Although most machine learning models are geared toward prediction rather than causal relationships between variables, confounding becomes a significant issue when feedback loops are generated and predictions are made using confounded data.