Personal predictive model based on systemic inflammation markers for estimation of postoperative pancreatic fistula following pancreaticoduodenectomy

Table 2 The operating characteristic curve analyses for each machine learning-based model

Model	AUC		No. of candidate variables
	Mean	95%CI
RFC	0.897	0.370–1.424	7
SVM	0.726	0.191–1.261	8
DT	0.807	0.250–1.364	8
ANN	0.882	0.321–1.443	7
XGboost	0.793	0.270–1.316	9

95%CI: 95% confidence interval; RFC: Random forest classifier; SVM: Support vector machine; DT: Decision tree; ANN: Artificial neutral network; XGboost: Extreme gradient boosting; AUC: Area under curve.