Fig. 4 | Scientific Reports

Fig. 4

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

Fig. 4

Diagnostic performances of multiple urinary RNA biomarker-based ML analysis on PSA gray zone patients. Among the patient cohort, 96 patients (24 BPH, 72 PCa) with serum PSA levels of 3–10 ng/mL were selected for analysis. (a, b) ROC curves for six different ML algorithms using the 3-feature combination (a) and the 9-feature combination (b). 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 (a) and (b). (d) Stratified-K-Fold cross-validation (K = 24) scores calculated for the trained ML classifiers in (a) and (b).

Back to article page