Machine-learning-based prediction model for Clavien-Dindo grade ≥ II complications after neoadjuvant therapy and laparoscopic gastrectomy in gastric cancer

Figure 1 Flow chat for study design. LASSO: Least absolute shrinkage and selection operator; NNE: Neural network ensemble; ROC: Receiver operating characteristic; SHAP: SHapley Additive exPlanations.

Figure 2 Least absolute shrinkage and selection operator regression results. A: Least absolute shrinkage and selection operator regression cross-validation curve; B: Key variables for least absolute shrinkage and selection operator regression screening. LASSO: Least absolute shrinkage and selection operator; ASA: American Society of Anesthesiologists; NRS: Nutritional Risk Screening; A/G: Albumin-to-globulin ratio.

Figure 3 Receiver operating characteristic curves of the machine learning prediction models. ROC: Receiver operating characteristic; AUC: Area under the curve.

Figure 4  Decision curve analysis curves of the machine learning prediction models.

Figure 5  Calibration curves of the machine learning prediction models.

Figure 6 SHapley Additive exPlanations feature importance in neural network ensemble. NNE: Neural network ensemble; SHAP: SHapley Additive exPlanations; NRS: Nutritional Risk Screening; ASA: American Society of Anesthesiologists.