Table 6.
Algorithmf | Accuracya | Recallb | Precisionc | Specificityd | NPVe |
---|---|---|---|---|---|
ADID + LLM | 80% | 90% | 82% | 57% | 72% |
Decision tree | 63% | 76% | 72% | 35% | 40% |
PAM | 81% | 90% | 83% | 61% | 74% |
SVM | 84% | 94% | 84% | 61% | 82% |
a Accuracy is the fraction of correctly classified patients and overall classified patients.
b Recall is the fraction of correctly classified good outcome patients and the overall predicted good outcome patients.
c Precision is the fraction of correctly classified good outcome patients and the predicted good outcome patients.
d Specificity is the fraction of correctly classified poor outcome patients and the overall poor outcome patients.
e NPV(negative predictive value) is the fraction of correctly classified poor outcome patients and the overall predicted poor outcome patients.
f Machine learning algorithms utilized for comparison.