Diagnostic Pathology

Table 3 Comparison of the performance and discriminative ability between the current and other models

From: Machine learning-based model for predicting the esophagogastric variceal bleeding risk in liver cirrhosis patients

Cohort	Models	1-year risk of EGVB
Cohort	Models	AUROC (95% CI)	C-index (95% CI)
Training	ANN	0.959 (0.945–0.973)	0.956 (0.728–0.972)
	NIEC	0.669 (0.605–0.731)	0.717 (0.646–0.735)
	Rev-NIEC	0.725 (0.669–0.780)	0.681 (0.636–0.726)
Validation	ANN	0.945 (0.877–0.987)	0.936 (0.753–0.965)
	NIEC	0.743 (0.600–0.887)	0.707 (0.643–0.772)
	Rev-NIEC	0.797 (0.667–0.927)	0.701 (0.631–0.771)

Abbreviations: ANN Artificial neural networks, AUROC Area under the receiver operating characteristic curves, CI Confidence interval, C-index Concordance index, EGVB Esophagogastric variceal bleeding, NIEC North Italian Endoscopic Club, Rev-NIEC Revised North Italian Endoscopic Club

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ISSN: 1746-1596

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