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Comparison of different classifiers for cancer diagnosis using image-level features alone
| Classifier | AUC | Accuracy | Sensitivity | Specificity | PPV | NPV |
|---|---|---|---|---|---|---|
| SVM | 0.955 | 86.9% | 89.5% | 89.0% | 85.1% | 89.0% |
| Random Forest | 0.924 | 85.1% | 84.3% | 91.0% | 79.9% | 91.0% |
| Naive Bayes | 0.852 | 72.8% | 81.5% | 81.0% | 62.6% | 84.0% |
| KNN | 0.818 | 81.8% | 81.7% | 82.0% | 81.7% | 82.0% |
| Decision Tree | 0.808 | 58.5% | 82.5% | 80.0% | 31.1% | 90.0% |
| LDA | 0.786 | 78.5% | 78.2% | 79.0% | 78.2% | 79.0% |
