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--- |
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library_name: transformers |
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tags: |
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- contrastive-learning |
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- Spanish-UMLS |
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- Hierarchical-enrichment |
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- entity-linking |
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- biomedical |
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- spanish |
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license: mit |
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language: |
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- es |
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base_model: |
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- PlanTL-GOB-ES/roberta-base-biomedical-clinical-es |
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--- |
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# HERBERT: Leveraging UMLS Hierarchical Knowledge to Enhance Clinical Entity Normalization in Spanish |
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**HERBERT-P** is a contrastive-learning-based bi-encoder for medical entity normalization in Spanish, leveraging synonym and parent relationships from UMLS to enhance candidate retrieval for entity linking in clinical texts. |
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**Key features:** |
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- Base model: [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) |
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- Trained with 15 positive pairs per anchor (synonyms + parents) |
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- Task: Normalization of disease, procedure, and symptom mentions to SNOMED-CT/UMLS codes. |
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- Domain: Spanish biomedical/clinical texts. |
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- Corpora: DisTEMIST, MedProcNER, SympTEMIST. |
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--- |
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## Benchmark Results |
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| Corpus | Top-1 | Top-5 | Top-25 | Top-200 | |
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|-------------|--------|--------|--------|---------| |
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| DisTEMIST | 0.574 | 0.720 | 0.803 | 0.869 | |
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| SympTEMIST | 0.630 | 0.779 | 0.881 | 0.945 | |
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| MedProcNER | 0.651 | 0.763 | 0.838 | 0.892 | |
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