Association of prealbumin with risk of abdominal surgery and endoscopic recurrence in Crohn’s disease: A machine learning study

Figure 5 Comparison of the predictive performance of the eight models for abdominal surgery and postoperative endoscopic recurrence. A: Harrell’s concordance index (C-index) of the eight models for predicting abdominal surgery in the training and validation cohorts; B: C-index of the eight models for predicting postoperative endoscopic recurrence in the training and validation cohorts. The evaluated models were Cox proportional hazards regression, random survival forest, gradient boosting machine, CoxBoost, survival support vector machine, XGBoost, SuperPC, and partial least squares regression for Cox models. RSF: Random survival forest; GBM: Gradient boosting machine; PLSR-Cox: Partial least squares regression for Cox models; SVM: Support vector machine.