Liver Disorders
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Counterfactual Explanation | liver-disorders | Validity100 | 20 | |
| Classification | Liver Disorders (10-fold cross-validation) | AUC70 | 12 | |
| Downstream ML Utility | Liver Disorders | F1-score99 | 8 | |
| Tabular Synthetic Data Generation | Liver Disorders | KS Statistic0.017 | 8 | |
| Counterfactual Proximity | liver-disorders | Mean Euclidean Distance0.15 | 8 | |
| Tabular Data Generation | Liver Disorders | Peak GPU Memory Usage (GB)2.1 | 7 | |
| Tabular Data Synthesis | Liver Disorders | SDMetrics Quality Score89 | 6 | |
| Synthetic Data Generation | Liver Disorders | Average Runtime (seconds)0.0127 | 5 | |
| Regression | Liver Disorders | Mean Relative Improvement (%)370 | 5 | |
| Counterfactual Generation | liver-disorders | Diversity1.36 | 4 | |
| Counterfactual Explanation Diversity | liver-disorders | Diversity2.3 | 4 | |
| Counterfactual Explanation | liver-disorders | Proximity Score2.4 | 4 | |
| Outlier Explanation | liver-disorders | Average Run Time (seconds)0.0018 | 4 | |
| Classification | Liver Disorders | Balanced Accuracy76 | 3 | |
| Heteroscedastic Regression | Liver Disorders | Coverage @ 95%91.3 | 3 | |
| Symbolic Distillation | Liver Disorders | Mean R^20.0877 | 3 | |
| Clustering | Liver Disorders | Cluster Assignment Mismatch44.93 | 3 | |
| Clustering | Liver Disorders | Regression Coefficient Difference1.5192 | 3 | |
| LPC Optimization | Liver Disorders UCI ID 60 | SSE94.9041 | 3 | |
| Clinical Validity Assessment | Liver Disorders | Factuality1 | 2 | |
| Privacy Risk Evaluation | Liver Disorders | B-B AUC60 | 2 |
Showing 21 of 21 rows