Circulatory Failure On Hirid
Métriques
AUPRC
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AUPRC | Paper Title | Repository |
|---|---|---|---|
| LSTM | 0.32.2±0.008 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
| LGBM | 0.389±0.003 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
| LGBM ( + hand crafted features) | 0.388±0.002 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
| TCN | 0.35.8±0.006 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
| Temporal Label Smoothing | 0.406±0.003 | Temporal Label Smoothing for Early Event Prediction | - |
| GRU | 0.368±0.005 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
| Transformer | 0.352±0.006 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
| LR | 0.305±0.000 | HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data | - |
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