Table 2.

AUC results using 4 algorithms, PSA and fPSA/fPSA in the validation cohort

AUC(95%CI)	Validation cohort	Changhai cohort	Zhongda cohort
LR	0.816 (0.78–0.85)	0.793 (0.75–0.83)	0.848 (0.80–0.90)
RF	0.779 (0.74–0.81)	0.766 (0.72–0.81)	0.844 (0.79–0.90)
XGBoost	0.795 (0.76–0.83)	0.763 (0.71–0.81)	0.817 (0.76–0.87)
AutoML	0.820 (0.79–0.85)	0.807 (0.76–0.85)	0.850 (0.80–0.89)
PSA	0.616 (0.57–0.66)	0.593 (0.54–0.65)	0.583 (0.51–0.65)
fPSA/PSA	0.675 (0.63–0.72)	0.675 (0.62–0.73)	0.738 (0.67–0.80)

AUC Area under receiver operating characteristic, AutoML Automated machine learning, LR Logistic regression, RF Random forest