From: Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU
Model | Overall performance | Discrimination | ||||||
---|---|---|---|---|---|---|---|---|
Brier score | 95% CI | AUROC | 95% CI | Sensitivity | 95% CI | Specificity | 95% CI | |
LASSO | 0.108 | 0.107–0.109 | 0.829 | 0.827–0.831 | 0.744 | 0.721–0.767 | 0.754 | 0.731–0.777 |
GBM | 0.104 | 0.102–0.105 | 0.845 | 0.837–0.853 | 0.771 | 0.750–0.792 | 0.755 | 0.722–0.789 |
RF | 0.109 | 0.108–0.109 | 0.829 | 0.823–0.834 | 0.765 | 0.756–0.774 | 0.740 | 0.719–0.761 |
LR | 0.107 | 0.105–0.108 | 0.833 | 0.830–0.838 | 0.760 | 0.740–0.780 | 0.748 | 0.724–0.772 |
SAPS II | 0.146 | 0.142–0.150 | 0.77 | 0.760–0.780 | 0.697 | 0.668–0.725 | 0.714 | 0.695–0.734 |