Table 2.

Summary of model performance metrics.

Metric model	Accuracy	Precision	Recall	F1	AUC
LR	0.6719 ± 0.0530	0.7196 ± 0.0499	0.7058 ± 0.0711	0.7106 ± 0.0492	0.7350 ± 0.0511
MLP	0.6714 ± 0.0479	0.6883 ± 0.0447	0.7896 ± 0.0820	0.7325 ± 0.0430	0.7333 ± 0.0515
RF	0.6588 ± 0.0470	0.7162 ± 0.0460	0.6750 ± 0.0740	0.6926 ± 0.0489	0.7079 ± 0.0545
SVM	0.6717 ± 0.0482	0.7196 ± 0.0475	0.7049 ± 0.0654	0.7103 ± 0.0451	0.7324 ± 0.0493
TRACK	0.6278 ± 0.0470	0.7061 ± 0.0511	0.6049 ± 0.0672	0.6495 ± 0.0503	0.6757 ± 0.0518
TRUST	0.6189 ± 0.0526	0.6491 ± 0.0459	0.7494 ± 0.1453	0.6840 ± 0.0890	0.6622 ± 0.0519

AUC=area under the curve; LR=logistic regression; MLP=multi-layer perceptron; RF=random forest; SVM=support vector machine; TRACK=Transfusion Risk and Clinical Knowledge; TRUST=Transfusion Risk Understanding Scoring Tool