Factual outcome prediction on MIMIC-III extract
9.05RMSECT
Evaluation results
| Method | Links | |
|---|---|---|
| CTTraining samples (N)=3000, Prediction window (τ)=22024.05 | 9.05 | |
| IGC-NetTraining samples (N)=3000, Prediction window (τ)=22024.05 | 9.14 | |
| CTTraining samples (N)=2000, Prediction window (τ)=22024.05 | 9.26 | |
| CRNTraining samples (N)=3000, Prediction window (τ)=22024.05 | 9.28 | |
| CTTraining samples (N)=1000, Prediction window (τ)=22024.05 | 9.32 | |
| IGC-NetTraining samples (N)=2000, Prediction window (τ)=22024.05 | 9.32 | |
| IGC-NetTraining samples (N)=1000, Prediction window (τ)=22024.05 | 9.42 | |
| CRNTraining samples (N)=2000, Prediction window (τ)=22024.05 | 9.61 | |
| CTTraining samples (N)=3000, Prediction window (τ)=32024.05 | 9.68 | |
| CRNTraining samples (N)=1000, Prediction window (τ)=22024.05 | 9.76 | |
| IGC-NetTraining samples (N)=3000, Prediction window (τ)=32024.05 | 9.76 | |
| CTTraining samples (N)=2000, Prediction window (τ)=32024.05 | 9.87 | |
| IGC-NetTraining samples (N)=2000, Prediction window (τ)=32024.05 | 9.88 | |
| CRNTraining samples (N)=3000, Prediction window (τ)=32024.05 | 9.93 | |
| CTTraining samples (N)=1000, Prediction window (τ)=32024.05 | 10.02 | |
| IGC-NetTraining samples (N)=1000, Prediction window (τ)=32024.05 | 10.03 | |
| CTTraining samples (N)=3000, Prediction window (τ)=42024.05 | 10.04 | |
| IGC-NetTraining samples (N)=3000, Prediction window (τ)=42024.05 | 10.07 | |
| IGC-NetTraining samples (N)=2000, Prediction window (τ)=42024.05 | 10.2 | |
| CTTraining samples (N)=2000, Prediction window (τ)=42024.05 | 10.23 | |
| CRNTraining samples (N)=2000, Prediction window (τ)=32024.05 | 10.26 | |
| CRNTraining samples (N)=3000, Prediction window (τ)=42024.05 | 10.28 | |
| IGC-NetTraining samples (N)=3000, Prediction window (τ)=52024.05 | 10.3 | |
| CTTraining samples (N)=3000, Prediction window (τ)=52024.05 | 10.32 | |
| IGC-NetTraining samples (N)=1000, Prediction window (τ)=42024.05 | 10.43 | |
| CTTraining samples (N)=1000, Prediction window (τ)=42024.05 | 10.44 | |
| CRNTraining samples (N)=1000, Prediction window (τ)=32024.05 | 10.45 | |
| IGC-NetTraining samples (N)=2000, Prediction window (τ)=52024.05 | 10.49 | |
| CTTraining samples (N)=2000, Prediction window (τ)=52024.05 | 10.53 | |
| CTTraining samples (N)=3000, Prediction window (τ)=62024.05 | 10.54 | |
| CRNTraining samples (N)=3000, Prediction window (τ)=52024.05 | 10.56 | |
| CRNTraining samples (N)=2000, Prediction window (τ)=42024.05 | 10.61 | |
| IGC-NetTraining samples (N)=3000, Prediction window (τ)=62024.05 | 10.62 | |
| IGC-NetTraining samples (N)=1000, Prediction window (τ)=52024.05 | 10.71 | |
| IGC-NetTraining samples (N)=2000, Prediction window (τ)=62024.05 | 10.73 | |
| CTTraining samples (N)=1000, Prediction window (τ)=52024.05 | 10.76 | |
| CTTraining samples (N)=2000, Prediction window (τ)=62024.05 | 10.76 | |
| CRNTraining samples (N)=3000, Prediction window (τ)=62024.05 | 10.78 | |
| CRNTraining samples (N)=1000, Prediction window (τ)=42024.05 | 10.82 | |
| TE-CDETraining samples (N)=3000, Prediction window (τ)=22024.05 | 10.82 | |
| CRNTraining samples (N)=2000, Prediction window (τ)=52024.05 | 10.9 | |
| IGC-NetTraining samples (N)=1000, Prediction window (τ)=62024.05 | 10.92 | |
| CTTraining samples (N)=1000, Prediction window (τ)=62024.05 | 11 | |
| TE-CDETraining samples (N)=2000, Prediction window (τ)=22024.05 | 11.05 | |
| RMSNsTraining samples (N)=2000, Prediction window (τ)=22024.05 | 11.07 | |
| CRNTraining samples (N)=1000, Prediction window (τ)=52024.05 | 11.08 | |
| CRNTraining samples (N)=2000, Prediction window (τ)=62024.05 | 11.13 | |
| TE-CDETraining samples (N)=3000, Prediction window (τ)=32024.05 | 11.13 | |
| CRNTraining samples (N)=1000, Prediction window (τ)=62024.05 | 11.28 | |
| RMSNsTraining samples (N)=1000, Prediction window (τ)=22024.05 | 11.32 | |
| TE-CDETraining samples (N)=2000, Prediction window (τ)=32024.05 | 11.35 | |
| RMSNsTraining samples (N)=3000, Prediction window (τ)=22024.05 | 11.38 | |
| TE-CDETraining samples (N)=3000, Prediction window (τ)=42024.05 | 11.39 | |
| G-transformerTraining samples (N)=1000, Prediction window (τ)=22024.05 | 11.46 | |
| G-NetTraining samples (N)=1000, Prediction window (τ)=22024.05 | 11.46 | |
| TE-CDETraining samples (N)=1000, Prediction window (τ)=22024.05 | 11.52 | |
| TE-CDETraining samples (N)=3000, Prediction window (τ)=52024.05 | 11.55 | |
| G-transformerTraining samples (N)=2000, Prediction window (τ)=22024.05 | 11.55 | |
| G-transformerTraining samples (N)=3000, Prediction window (τ)=22024.05 | 11.58 | |
| TE-CDETraining samples (N)=2000, Prediction window (τ)=42024.05 | 11.6 | |
| TE-CDETraining samples (N)=3000, Prediction window (τ)=62024.05 | 11.7 | |
| TE-CDETraining samples (N)=2000, Prediction window (τ)=52024.05 | 11.77 | |
| TE-CDETraining samples (N)=1000, Prediction window (τ)=32024.05 | 11.82 | |
| G-NetTraining samples (N)=2000, Prediction window (τ)=22024.05 | 11.87 | |
| G-NetTraining samples (N)=3000, Prediction window (τ)=22024.05 | 11.9 | |
| TE-CDETraining samples (N)=2000, Prediction window (τ)=62024.05 | 11.92 | |
| TE-CDETraining samples (N)=1000, Prediction window (τ)=42024.05 | 12.05 | |
| RMSNsTraining samples (N)=2000, Prediction window (τ)=32024.05 | 12.21 | |
| TE-CDETraining samples (N)=1000, Prediction window (τ)=52024.05 | 12.23 | |
| TE-CDETraining samples (N)=1000, Prediction window (τ)=62024.05 | 12.36 | |
| RMSNsTraining samples (N)=1000, Prediction window (τ)=32024.05 | 12.37 | |
| G-transformerTraining samples (N)=2000, Prediction window (τ)=32024.05 | 12.68 | |
| RMSNsTraining samples (N)=2000, Prediction window (τ)=52024.05 | 12.71 | |
| G-transformerTraining samples (N)=1000, Prediction window (τ)=32024.05 | 12.77 | |
| G-transformerTraining samples (N)=3000, Prediction window (τ)=32024.05 | 12.78 | |
| RMSNsTraining samples (N)=2000, Prediction window (τ)=62024.05 | 12.8 | |
| RMSNsTraining samples (N)=2000, Prediction window (τ)=42024.05 | 12.82 | |
| G-NetTraining samples (N)=1000, Prediction window (τ)=32024.05 | 12.94 | |
| RMSNsTraining samples (N)=3000, Prediction window (τ)=32024.05 | 12.95 | |
| RMSNsTraining samples (N)=1000, Prediction window (τ)=42024.05 | 13.09 | |
| G-NetTraining samples (N)=3000, Prediction window (τ)=32024.05 | 13.17 | |
| G-NetTraining samples (N)=2000, Prediction window (τ)=32024.05 | 13.2 | |
| G-transformerTraining samples (N)=2000, Prediction window (τ)=42024.05 | 13.32 | |
| RMSNsTraining samples (N)=3000, Prediction window (τ)=42024.05 | 13.4 | |
| G-transformerTraining samples (N)=3000, Prediction window (τ)=42024.05 | 13.43 | |
| RMSNsTraining samples (N)=3000, Prediction window (τ)=52024.05 | 13.48 | |
| G-transformerTraining samples (N)=1000, Prediction window (τ)=42024.05 | 13.56 | |
| RMSNsTraining samples (N)=1000, Prediction window (τ)=52024.05 | 13.57 | |
| RMSNsTraining samples (N)=3000, Prediction window (τ)=62024.05 | 13.59 | |
| G-transformerTraining samples (N)=2000, Prediction window (τ)=52024.05 | 13.75 | |
| G-transformerTraining samples (N)=3000, Prediction window (τ)=52024.05 | 13.82 | |
| G-NetTraining samples (N)=1000, Prediction window (τ)=42024.05 | 13.9 | |
| RMSNsTraining samples (N)=1000, Prediction window (τ)=62024.05 | 13.94 | |
| G-NetTraining samples (N)=3000, Prediction window (τ)=42024.05 | 13.96 | |
| G-NetTraining samples (N)=2000, Prediction window (τ)=42024.05 | 14.02 | |
| G-transformerTraining samples (N)=1000, Prediction window (τ)=52024.05 | 14.07 | |
| G-transformerTraining samples (N)=3000, Prediction window (τ)=62024.05 | 14.14 | |
| G-transformerTraining samples (N)=2000, Prediction window (τ)=62024.05 | 14.16 | |
| G-transformerTraining samples (N)=1000, Prediction window (τ)=62024.05 | 14.44 | |
| G-NetTraining samples (N)=1000, Prediction window (τ)=52024.05 | 14.53 |