A Metabolism-Based Interpretable Machine Learning Prediction Model for Diabetic Retinopathy Risk: A Cross-Sectional Study in Chinese Patients with Type 2 Diabetes

Figure 6

SHAP dependence plots of important features in XGBoost model. (a) SHAP dependence plots of duration of type 2 diabetes; (b) SHAP dependence plots of C18 : 1OH; (c) SHAP dependence plots of phenylalanine; (d) SHAP dependence plots of C18 : 1; (e) SHAP dependence plots of threonine; (f) SHAP dependence plots of total cholesterol; (g) SHAP dependence plots of tyrosine. The blue dots represent the eigenvalues and the Shapley values corresponding to each observation. The red line represents the Shapley values equal to zero. When the Shapely value corresponding to a characteristic was greater than zero, the risk of developing DR is considered to be increased under that condition. C18 : 1OH: 3-hydroxy-octadecylcarnitine; C18 : 1; octacarbonylcarnitine; C18 : 2: octadecadienylcarnitine; SHAP: Shapley Additive exPlanation.

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