Development and prospective validation of a machine learning model to predict mortality in cirrhosis with esophageal variceal bleeding

Table 2 Prediction using machine learning

Model	Sensitivity (recall)	Specificity	Accuracy
Logistic regression	0.67	0.71	0.69
Random forest	0.80	0.86	0.83
SVM	0.73	0.64	0.69
Naive bayes	0.93	0.21	0.59
Decision tree	0.53	0.79	0.66
MLP	0.67	0.86	0.76

Comparison of model performance metrics across different machine learning algorithms in the development cohort. Sensitivity represents the true-positive rate, specificity the true-negative rate, and accuracy the overall correct classification rate. MLP: Multilayer perceptron; SVM: Support vector machine.