Additional file 6 of Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables
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Additional file 6: Confusion matrixes, confidence intervals and ROC curves for the remaining four ML algorithms (KNN, SVM, Logistic regression, Decision Tree). The following sets of variables were considered: (i) proteomic + clinical (named “Multivariate Analysis”, blue), (ii) proteomic variables only (named “Peptides Analysis”, green), (iii) clinical variables only (named “Biological Samples”, red), (iv) PSA only (named “Univariate Analysis”, red).
提供机构：
Rota, Maria Antonietta; Aracri, Federica; Veltri, Pierangelo; Damiano, Rocco; Cuda, Giovanni; Prestagiacomo, Licia Elvira; Guzzi, Pietro Hiram; Alba, Stefano; Gabriele, Caterina; Tradigo, Giuseppe; Gaspari, Marco
创建时间：
2024-08-14
