Interpretable multimodal artificial intelligence model for predicting advanced neoplasia in pancreatic cystic lesions

Figure 1 Area under the curve comparison of prediction models and guideline-based criteria. Bar plot illustrating the discriminative performance of the integrated multimodal model and the core clinical-endoscopic ultrasound model in the validation cohort (n = 56; 17 advanced neoplasia, 39 non-advanced), alongside the area under the curve (AUC) values of international guideline-based criteria (American Gastroenterological Association 2015, Fukuoka 2017, European 2018, Kyoto 2024). The integrated multimodal model demonstrated the highest AUC (0.91), followed by the core model (0.87). Guideline-based criteria showed lower discriminative performance (AUC range: 0.70-0.79). The Kyoto 2024 AUC reflects evaluation within the intraductal papillary mucinous neoplasm subset (n = 161), consistent with its intended scope. AGA: American Gastroenterological Association; AUC: Area under the curve.