Lung cancer stage detection on NSCLC Radiomics dataset
90.22AccuracyGL-RFE + DNN
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| GL-RFE + DNNModel Type=Deep Learning2026.06 | 90.22 | 90.1 | 90.24 | 90.19 | |
| Autoencoder + ClassifierModel Type=Deep Learning2026.06 | 89.1 | 88.7 | 89.5 | 89 | |
| CNN (Radiomics Input)Model Type=Deep Learning2026.06 | 88.5 | 88 | 89.1 | 88.5 | |
| Random Forest (RF)Model Type=Ensemble ML2026.06 | 88 | 87 | 89 | 88 | |
| ANN (MLP)Model Type=Deep Learning2026.06 | 87 | 86 | 88 | 87 | |
| SVMModel Type=Classical ML2026.06 | 86.2 | 85.9 | 86.5 | 86.1 | |
| Logistic RegressionModel Type=Classical ML2026.06 | 85.6 | 85.2 | 85.9 | 85.5 | |
| KNNModel Type=Classical ML2026.06 | 84.75 | 84.1 | 85 | 84.5 |