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Table 3 Predictive performance of nomogram and machine learning algorithms

From: Development and validation of a novel predictive model and web calculator for evaluating transfusion risk after spinal fusion for spinal tuberculosis: a retrospective cohort study

Model Average AUC Maximum AUC Average Accuracy
Nomogram 0.75 0.93  
Support vector machine 0.62 0.68 0.62
K-nearest neighbors 0.65 0.77 0.71
Decision tree 0.56 0.60 0.64
Naive Bayesian 0.74 0.88 0.73
Multilayer perceptron 0.56 0.63 0.65
Random Forest 0.72 0.83 0.75