Table 3 RF accuracy measures for early sepsis detection. The results from Table 2 are included in this table as the “no shift” (e.g. zero shift) to put the sepsis detection at clinical determination time versus early sepsis detection in context. Utility is the additional evaluation metric5 that measures how well the model is doing at early sepsis detection.
From: Exploring a global interpretation mechanism for deep learning networks when predicting sepsis
Accuracy (%) | Precision (%) | Specificity (%) | Recall/sensitivity (%) | F1 score | Mathew’s coefficient | Utility | |
|---|---|---|---|---|---|---|---|
No shift (Table 1) | |||||||
RF | 99.0 | 92.5 | 99.9 | 56.3 | 0.70 | 0.92 | 0.83 |
1-Hour shift | |||||||
RF | 99.0 | 93.6 | 99.8 | 60.4 | 0.73 | 0.93 | 0.82 |
6-Hour shift | |||||||
RF | 99.0 | 95.8 | 99.8 | 71.4 | 0.82 | 0.95 | 0.89 |
12-Hour shift | |||||||
RF | 99.0 | 97.0 | 99.8 | 78.8 | 0.87 | 0.96 | 0.88 |
