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. 2023 Jul 7;13:11005. doi: 10.1038/s41598-023-38257-9

Figure 2.

Figure 2

Violin plots showing the AUROC performance comparison between logistic regression (LR) and random forest (RF) with different inputs: diagnostic codes only (Diag), lab results only (Labs) integration of both diagnostic codes and lab results (LabsDiag) and integration of diagnostic codes, lab results and demographic features (LabsDiagDemo). The p-values obtained by a paired Wilcoxon signed-rank test (top of the plots) shows that RF outperforms LR significantly in every case.