Table 4.
Method | Matthews’ correlation coefficient (MCC) | Accuracy | Sensitivity | Specificity | AUC | P-value |
---|---|---|---|---|---|---|
PIP-EL | 0.435 | 0.717 | 0.701 | 0.727 | 0.786 | – |
Extremely randomized trees (ERT) | 0.423 | 0.712 | 0.714 | 0.709 | 0.775 | 0.538 |
Support vector machine (SVM) | 0.298 | 0.649 | 0.618 | 0.679 | 0.697 | <0.000003 |
ProInflam | 0.580 | 0.778 | 0.936 | 0.620 | 0.880 | – |
The first column represents the methods developed in this study. The column 2–6 respectively represent the MCC, accuracy, sensitivity, specificity, and AUC value. The last column represents a pairwise comparison of AUC between PIP-EL and the other methods using a two-tailed t-test. P ≤ 0.05 indicates a statistically meaningful difference between PIP-EL and the selected composition (shown in bold). For comparison, we have also included ProInflam CV performance.