Fig. 1 | Scientific Reports

Fig. 1

From: Prostate cancer diagnosis using sensitive and sophisticated machine learning classifiers based on non-invasive urinary RNA biomarkers (PCASSO)

Fig. 1

Characterization of candidate urinary RNA biomarkers of PCa. (a) AUC values for single urinary RNA biomarkers for the diagnosis of PCa. ROC curves were constructed from expression levels for single urinary RNA biomarkers (Supplementary Fig. 1). (b) ROC curves for single urinary RNA biomarkers with six different ML classifiers. Each ML model was trained on the training dataset and ROC curves were constructed on the test set. (c) AUC values for the ROC curves in (b). (d) Stratified-K-Fold cross-validation (K = 51) scores. This unbiased indicator maintains the ratio of PCa to BPH in each fold.

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