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Prediction of incisional hernia using combined three optimal biomarkers, using three machine learning classifiers: ensemble boosting, random forest, SVM
| Classifier | Accuracy | Sensitivity | Specificity | AUC |
|---|---|---|---|---|
| Ensemble boosting | 0.83 | 0.86 | 0.81 | 0.85 |
| Random forest | 0.79 | 0.76 | 0.81 | 0.83 |
| SVM | 0.67 | 0.67 | 0.67 | 0.68 |
The ensemble boosting classifier model had the best performance in terms of accuracy, sensitivity, specificity, and AUC (bolded)
SVM Support vector machine, AUC area under the curve
