Table 3 Detailed results of machine learning classifiers for prediction of mortality and post-surgery prolonged LOS.
From: Deep Learning for Improved Risk Prediction in Surgical Outcomes
Model | Precision | Recall | F-Score | Accuracy | AUROC |
|---|---|---|---|---|---|
Mortality Prediction | |||||
Deep Neural Network | 0.94 ± 0.03 | 0.86 ± 0.04 | 0.89 ± 0.03 | 0.89 ± 0.04 | 0.95 ± 0.02 |
Gradient Boosting | 0.87 ± 0.03 | 0.78 ± 0.04 | 0.83 ± 0.04 | 0.84 ± 0.04 | 0.90 ± 0.04 |
Random Forest | 0.71 ± 0.04 | 0.27 ± 0.03 | 0.43 ± 0.03 | 0.75 ± 0.05 | 0.84 ± 0.03 |
Decision Tree | 0.43 ± 0.04 | 0.14 ± 0.05 | 0.29 ± 0.06 | 0.65 ± 0.04 | 0.58 ± 0.04 |
Ridge Regression | 0.43 ± 0.04 | 0.10 ± 0.04 | 0.28 ± 0.03 | 0.61 ± 0.04 | 0.55 ± 0.03 |
Prolonged LOS Prediction | |||||
Deep Neural Network | 0.85 ± 0.04 | 0.91 ± 0.04 | 0.89 ± 0.04 | 0.85 ± 0.03 | 0.94 ± 0.04 |
Gradient Boosting | 0.87 ± 0.04 | 0.82 ± 0.05 | 0.83 ± 0.03 | 0.82 ± 0.03 | 0.88 ± 0.03 |
Random Forest | 0.62 ± 0.03 | 0.51 ± 0.05 | 0.55 ± 0.04 | 0.61 ± 0.03 | 0.67 ± 0.03 |
Decision Tree | 0.56 ± 0.04 | 0.49 ± 0.04 | 0.52 ± 0.05 | 0.53 ± 0.04 | 0.59 ± 0.05 |
Ridge Regression | 0.59 ± 0.05 | 0.32 ± 0.04 | 0.35 ± 0.04 | 0.63 ± 0.06 | 0.54 ± 0.07 |
