Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei: A quantitative analysis
Fig 8
The receiver operating characteristic curves for the feature-based classification, where a true positive sample is a PTC-like sample classified as PTC-like.
All cross-validation splits and the resulting area under curve (AUC) together with the resulting mean for the dataset are shown. The standard deviation around the mean is annotated in dark gray. The red dotted line corresponds to the classification by chance.