Development of a deep learning model for guiding treatment decisions of acute variceal bleeding in patients with cirrhosis

Figure 3 Receiver operating characteristic curves and confusion matrix of different models for clinical outcomes in acute variceal bleeding patients. A-C: Receiver operating characteristic curves of seven models for 6-week treatment failure, 1-year mortality, intensive care unit (ICU) requirement, respectively, in the internal and external validation cohort; D-F: Confusion matrix for 6-week treatment failure, 1-year mortality, ICU requirement, respectively, in the internal and external validation cohort using artificial intelligence-acute variceal bleeding algorithms. True labels on the vertical axis and predicted labels on the horizontal axis. ICU: Intensive care unit; AUC: Area under the curve; SVM: Support vector machine; LR: Logistic regression; DT: Decision tree; RF: Random forest; XGB: Extreme gradient boosting; LGBM: Light gradient boosting machine; AVB: Acute variceal bleeding; AI: Artificial intelligence.