All Variables (23 Inputs) | Variables Selected by RF Importance (4 Inputs) | All Conventional Variables (6 Inputs) | Variables Selected by RF Importance: Conventional Only (4 Inputs) | |
---|---|---|---|---|
Random forest | 0.572 | 0.586 | 0.513 | 0.523 |
Linear | 0.542 | 0.572 | 0.444 | 0.475 |
Neural network | 0.265 | 0.460 | 0.382 | 0.379 |
Decision tree | 0.301 | 0.325 | 0.376 | 0.376 |
↵a The columns list variables used to train the predictive model. “All Variables” is simply using all 23 imaging parameters of all 6 conventional sequences, whereas “RF Importance” and “RF Importance, Conventional” use the final 4 variable sets shown in Online Tables 4 and 5. A larger average R2 indicated better performance.