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Table 3 Performance evaluation of models using the test set. The standard deviation is reported in round brackets

From: Machine learning models predicting multidrug resistant urinary tract infections using “DsaaS

Method AUC-ROC Accuracy AUC-PRC F1 score MCC Sensitivity Specificity
Catboost 0.739 (0.021) 0.717 (0.032) 0.853 (0.028) 0.809 (0.027) 0.909 (0.026) 0.904 (0.061) 0.343 (0.052)
SVM 0.628 (0.025) 0.630 (0.057) 0.752 (0.031) 0.702 (0.033) 0.810 (0.032) 0.823 (0.042) 0.254 (0.085)
NeuralNetworks 0.652 (0.023) 0.686 (0.019) 0.801 (0.024) 0.804 (0.016) 0.878 (0.024) 0.880 (0.077) 0.288 (0.075)
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