 as a function of the number of similar patients used in training.  ![](pone.0000000.t000){#pone.0000000.t000g}    Number of Similar Patients   AUROC (Mean \[00% CI\])   AUPRC (Mean \[00% CI\])   ---------------------------- ------------------------- -------------------------   0000                         0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   0000                         0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   0000                         0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   0000                         0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   0000                         0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]   00000                        0.000 \[0.000, 0.000\]    0.000 \[0.000, 0.000\]  The results shown in [Fig 0](#pone.0000000.g000){ref-type="fig"} are tabulated here. AUROC: area under the receiver operating characteristic curve; AUPRC: area under the precision-recall curve; CI: confidence interval.  ![Mortality prediction performance of personalized 