Table 2.
The receiver operating characteristic curve analyses for pain risk in each machine learning-based model
Model |
Training set
|
Testing set
|
||
AUC mean
|
AUC 95%CI
|
AUC mean
|
AUC 95%CI
|
|
RFM | 0.869 | 0.816-0.922 | 0.871 | 0.818-0.924 |
DTM | 0.861 | 0.808-0.914 | 0.864 | 0.811-0.917 |
ANNM | 0.826 | 0.773-0.879 | 0.827 | 0.774-0.880 |
SVMM | 0.803 | 0.750-0.856 | 0.808 | 0.755-0.861 |
NBM | 0.798 | 0.745-0.851 | 0.803 | 0.750-0.856 |
RFM: Random forest model; SVMM: Support vector machine model; DTM: Decision tree model; ANNM: Artificial neural network model; NBM: Naive Bayesian model; AUC: Area under curve; 95%CI: 95% confidence interval.