Endoscopic ultrasound-based deep learning for predicting chemotherapy response in unresectable pancreatic ductal adenocarcinoma

Table 6 Performance metrics of the carbohydrate antigen 19-9-based random forest model for chemotherapy response prediction in the training, internal validation, and independent test cohorts

Group	AUC (95%CI)	ACC (%) (95%CI)	SEN (%) (95%CI)	SPE (%) (95%CI)	PPV (%)	NPV (%)	FNR (%)	F1
Train	1.000	100.00	100.00	100.00	100.00	100.00	0	1.000
Val	0.517	76.97	9.09	95.80	37.50	79.17	90.91	0.146
Test	0.673 (0.445–0.877)	78.95 (65.79–92.11)	25.00 (0.00–60.00)	93.33 (83.33–100.00)	50.00	82.35	75.00	0.333

ACC: Accuracy; AUC: Area under the receiver operating characteristic curve; CI: Confidence interval; F1: F1-score; FNR: False negative rate; NPV: Negative predictive value; PPV: Positive predictive value; SEN: Sensitivity; SPE: Specificity; Train: Training cohort; Test: Independent test cohort; Val: Internal validation cohort.