Figure 6. The machine learning models encompassing FN1 and POSTN to diagnose CRS. (A) A nomogram was drawn to visualize the logistic regression model. (B) The confusion matrix showed the predictive performance of the logistic regression model. (C) The classification tree was established to diagnose CRS. (D) The confusion matrix of the classification tree model. (E) The mean decrease accuracy and mean decrease Gini of the features in the random forest model. (F) The confusion matrix exhibited that the random forest model could distinguish the CRS samples with high efficacy. Abbreviation: CRS: cardiorenal syndrome.