Table 2. The performance of the brain metastases prediction model (under 10-fold cross-validation mode).
Machine learning algorithm | AUC (95% confidence interval) | Accuracy | Precision | Sensitivity (%) | Specificity (%) | |
---|---|---|---|---|---|---|
Brain metastasis | Non-brain metastasis | |||||
Naive Bayes | 0.878 (0.743–0.911) | 0.786 | 0.800 | 0.773 | 76.2 | 81.0 |
LASSO regression | 0.739 (0.607–0.809) | 0.667 | 0.652 | 0.684 | 71.4 | 61.9 |
Support vector machine | 0.702 (0.592–0.797) | 0.631 | 0.617 | 0.649 | 69.0 | 57.1 |
Random forest | 0.695 (0.585–0.791) | 0.643 | 0.658 | 0.630 | 59.5 | 69.0 |
Neural network | 0.690 (0.580–0.786) | 0.702 | 0.698 | 0.707 | 71.4 | 69.0 |
K-nearest neighbors | 0.647 (0.535–0.748) | 0.607 | 0.600 | 0.615 | 64.3 | 57.1 |