Computed tomography-based deep learning and multi-instance learning for predicting microvascular invasion and prognosis in hepatocellular carcinoma

Table 4 Predictive metrics of various signatures

Dataset	Signature	Accuracy	AUC (95%CI)	Sensitivity	Specificity
Training	Clinical	0.530	0.655 (0.559-0.751)	0.882	0.313
Validation	Clinical	0.500	0.631 (0.470-0.793)	0.882	0.341
Training	Radiomics	0.687	0.770 (0.691-0.849)	0.765	0.639
Validation	Radiomics	0.672	0.727 (0.597-0.857)	0.882	0.585
Training	MIL	0.821	0.880 (0.821-0.940)	0.824	0.819
Validation	MIL	0.793	0.877 (0.784-0.970)	0.882	0.756

AUC: Area under the curve; CI: Confidence interval; MIL: Multi-instance learning.