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Models/HAN

HAN

Reported on 16 benchmarks across 6 tasks · 2 papers · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

Multi-Label Text ClassificationonMIMIC-III
Micro-F1· 2020-10-29
40.7
SOTA
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
ClassificationonMIMIC-III
Micro-F1· 2020-10-29
40.7
SOTA
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Multi-Label ClassificationonMIMIC-III
Macro-AUC· 2020-10-29
88.5
best: 96.2 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Multi-Label ClassificationonMIMIC-III
Macro-F1· 2020-10-29
3.6
best: 24.7 (PLM-CA)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Multi-Label ClassificationonMIMIC-III
Micro-AUC· 2020-10-29
98.1
best: 99.3 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Multi-Label ClassificationonMIMIC-III
Micro-F1· 2020-10-29
40.7
best: 61.2 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Multi-Label ClassificationonMIMIC-III
Precision@8· 2020-10-29
61.4
best: 77.7 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
ClassificationonarXiv-10
Accuracy
0.746
best: 0.794 (Protoformer)

Medical5 results

Medical Code PredictiononMIMIC-III
Macro-AUC· 2020-10-29
88.5
best: 96.2 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Medical Code PredictiononMIMIC-III
Macro-F1· 2020-10-29
3.6
best: 24.7 (PLM-CA)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Medical Code PredictiononMIMIC-III
Micro-AUC· 2020-10-29
98.1
best: 99.3 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Medical Code PredictiononMIMIC-III
Micro-F1· 2020-10-29
40.7
best: 61.2 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Medical Code PredictiononMIMIC-III
Precision@8· 2020-10-29
61.4
best: 77.7 (GKI-ICD)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728

Natural Language Processing3 results

Text ClassificationonMIMIC-III
Micro-F1· 2020-10-29
40.7
SOTA
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation arXiv:2010.15728
Visual Question Answering (VQA)onVQA-CP
Score· 2018-08-01
28.65
best: 58.95 (CSS)
SOTA
Learning Visual Question Answering by Bootstrapping Hard Attention arXiv:1808.00300
Text ClassificationonarXiv-10
Accuracy
0.746
best: 0.794 (Protoformer)