From: The application of unsupervised deep learning in predictive models using electronic health records
Scenarios | Prediction Models | Precision (%) (recall = 0.70) | PPV (%) (NPV = 0.95) | AUC | NO. |
---|---|---|---|---|---|
1. Raw Data | Autoencoder | 24.23 (0.18) | 19.93 (0.07) | 0.749 (0.01) | 50 (0.00) |
LASSO (λmin) | 28.25 (0.17) | 25.09 (0.05) | 0.788 (0.01) | 300 (0.06) | |
Random Forest | 25.63 (0.18) | 21.93 (0.06) | 0.767 (0.01) | 100 (0.00) | |
Simple Reg | 20.96 (0.20) | 15.73 (0.11) | 0.708 (0.02) | 12 (0.00) | |
Enhanced Reg | 24.62 (0.18) | 20.45 (0.07) | 0.754 (0.01) | 57 (0.03) | |
2. Correct Categories | Autoencoder | 25.07 (0.18) | 21.45 (0.07) | 0.757 (0.03) | 50 (0.00) |
LASSO (λmin) | 26.25 (0.17) | 22.94 (0.05) | 0.771 (0.01) | 132 (0.02) | |
Random Forest | 24.93 (0.18) | 21.57 (0.06) | 0.759 (0.01) | 136 (0.00) | |
Simple Reg | 21.36 (0.18) | 17.10 (0.09) | 0.713 (0.01) | 16 (0.00) | |
Enhanced Reg | 25.77 (0.17) | 22.32 (0.06) | 0.766 (0.01) | 60 (0.06) | |
3. Incorrect Categories | Autoencoder | 22.73 (0.18) | 18.82 (0.08) | 0.732 (0.01) | 60 (0.00) |
LASSO (λmin) | 24.07 (0.17) | 20.25 (0.06) | 0.748 (0.01) | 132 (0.02) | |
Random Forest | 22.70 (0.18) | 18.67 (0.07) | 0.733 (0.01) | 136 (0.00) | |
Simple Reg | 19.83 (0.19) | 15.31 (0.12) | 0.690 (0.02) | 16 (0.00) | |
Enhanced Reg | 23.61 (0.18) | 19.69 (0.07) | 0.743 (0.01) | 69 (0.03) | |
4. Incorrect Categories and Missing Data | Autoencoder | 24.16 (0.18) | 20.45 (0.07) | 0.748 (0.03) | 60 (0.00) |
LASSO (λmin) | 25.32 (0.17) | 21.67 (0.06) | 0.761 (0.01) | 175 (0.08) | |
Random Forest | 23.61 (0.18) | 19.92 (0.07) | 0.745 (0.01) | 226 (0.00) | |
Simple Reg | 20.92 (0.19) | 16.31 (0.10) | 0.706 (0.02) | 28 (0.00) | |
Enhanced Reg | 24.89 (0.17) | 21.25 (0.07) | 0.756 (0.02) | 81 (0.04) |