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. 2017 Jul;92(1):179–191. doi: 10.1016/j.kint.2017.01.017

Figure 3.

Figure 3

Local immune fingerprints in culture-negative episodes of peritonitis. (a) Performance of Random Forest (RF), Support Vector Machine (SVM), and artificial neural network (ANN)–based feature elimination models for the prediction of culture-negative episodes (no growth, N = 19) against microbiologically confirmed infections (other, N = 64), shown as area under the curve (AUC) depending on the number of biomarkers. Red symbols depict the maximum AUC for each model. (b) Kurtosis and skewness of the top 5 biomarkers selected by RF-based feature elimination. (c) Receiver operating characteristic analysis showing specificity and sensitivity of the top 5 biomarkers. (d) Tukey plots of the top 5 biomarkers in patients with culture-negative peritonitis and with infectious (other) episodes of peritonitis, as assessed by Mann-Whitney tests (***P < 0.001). (e) Heat map showing the top 5 biomarkers across all patients presenting with acute peritonitis. IL, interleukin; MMP, matrix metalloproteinase.