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The ROC curves for diagnosing pancreatic cancer by the ROSE-AI system using different data-augmentation techniques. The diagnostic performance for each data augmentation method is shown. The ROSE-AI system trained only with the augmented data using the geometric transformation technique had the highest diagnostic accuracy (AUC = 0.954). ROC, receiver operating characteristic; AUC, area under the curve; G, geometric transformations; C, color space transformations; K, kernel filtering.
