Development and validation of machine learning models for esophagogastric variceal bleeding risk in hepatocellular carcinoma patients

Figure 1 Technology roadmap. HCC: Hepatocellular carcinoma; SHAP: SHapley Additive exPlanation.

Figure 2 Schematic diagram of variable selection via LASSO regression analysis. A: Ten-fold cross-validation plot; B: Coefficient path diagram.

Figure 3 Receiver operating characteristic curves of six machine learning models on the validation set. ROC: Receiver operating characteristic; AUC: Area under the curve; XGBoost: Extreme gradient boosting; LightGBM: Light gradient boosting machine; SVM: Support vector machine; ANN: Artificial neural network.

Figure 4 Confusion matrices of six machine learning models on the validation set. A: Decision tree; B: Random forest; C: Extreme gradient boosting; D: Light gradient boosting machine; E: Support vector machine; F: Artificial neural network. EGVB: Esophagogastric variceal bleeding; XGBoost: Extreme gradient boosting; LightGBM: Light gradient boosting machine; SVM: Support vector machine; ANN: Artificial neural network.

Figure 5 The calibration curve and decision curve analysis curve of the support vector machine model in the validation set. A: Calibration curve; B: Decision curve analysis curve.

Figure 6 support vector machine model interpretable analysis SHapley Additive exPlanation plot. A: Feature importance bar chart; B: Swarm plot. The X-axis represents SHapley Additive exPlanation values, with positive values indicating an increased probability of esophagogastric variceal bleeding and negative values indicating a decreased probability. Dot colors represent feature values, ranging from low (blue) to high (red). Albumin, splenic vein diameter, and tumor burden score are continuous variables, while ascites is a binary variable. SHAP: SHapley Additive exPlanation.

Figure 7 Dependence plots of the support vector machine model. A-D: The X-axis represents feature values, and the Y-axis represents SHapley Additive exPlanation (SHAP) values (contribution to the predicted probability). Each dot denotes an individual sample. Positive SHAP values indicate an increased risk of esophagogastric variceal bleeding, while negative values indicate a decreased risk. SHAP: SHapley Additive exPlanation.

Figure 8  Waterfall plot of the support vector machine model.