Figure 4. SHAP value-based feature importance for prediction of depressive symptoms at 3 months follow-up based on Random Forest model trained onraw features, with (a) CESD or (b) MFQ as the outcome measure.

(Left) The barplot summarizes the overall impact of each feature on model output, ranked from the highest. (Right) The individual dot color corresponds to the value of the variable, and location on the plot’s x axis corresponds to that point’s relative impact on the model output. A high-feature value (red) with a corresponding high x axis value (SHAP value) represents a point that strongly, positively influences the model’s prediction of depression outcome.