Figure 9.

The SHAP method is used to analyze the important features of the XGBoost model. Create a point for each feature attribute value of each patient’s model, thereby assigning a point to each patient on the line for each feature. Dots are colored according to the eigenvalues of the corresponding patients and accumulate vertically to depict the density. Purple indicates high eigenvalues (death in this case), while yellow indicates low eigenvalues. The farther the point is from the baseline SHAP value, the greater the impact on the output.