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

Table 3 Performance metrics of the VGG19-BN model for chemotherapy response prediction in the training, 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	99.77	100.00	99.73	98.622	100.00	0	0.993
Val	0.864	90.36	66.67	94.99	72.24	93.58	33.33	0.693
Test	0.775 (0.705–0.841)	82.78 (79.05–85.89)	46.15 (32.43–59.02)	87.21 (83.72–90.19)	30.38	93.05	53.85	0.366

95% confidence intervals (CIs) for area under the receiver operating characteristic curve were computed using the DeLong method, whereas 95%CIs for accuracy, sensitivity, and specificity were computed using the Wilson score interval method. CIs are reported for the independent test cohort only. AUC: Area under the receiver operating characteristic curve; ACC: Accuracy; 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.