Fig. 5

SHAP-based interpretation for the RF model. A The Beeswarm plot depicts the influence of the seven features across all model samples. Combining feature importance and feature effect, Beeswarm ranks the features according to the sum of the SHAP across all samples (y-axis). One row in the plot represents one feature, and each dot represents the feature Shapley value for one sample; colors represent feature values (purple for high, yellow for low). Long tails indicate that patient characteristics are of the utmost importance. The x-axis represents the influence on the model’s output, with positive values increasing risk and negative values decreasing risk. B Features are ranked according to the mean absolute Shapley values. C–I SHAP dependence plots show predicted risk versus feature value. SHAP shapley additive explanations, RF random forest, GCS glasgow coma scale, ISS injury severity score, BE base excess, BMI body mass index