---
library_name: transformers
tags:
  - contrastive-learning
  - Spanish-UMLS
  - Hierarchical-enrichment
  - entity-linking
  - biomedical
  - spanish
license: mit
language:
  - es
base_model:
  - PlanTL-GOB-ES/roberta-base-biomedical-clinical-es
---

# HERBERT: Leveraging UMLS Hierarchical Knowledge to Enhance Clinical Entity Normalization in Spanish

**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.

**Key features:**
- Base model: [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es)
- Trained with 30 positive pairs per anchor (synonyms + parents)
- Task: Normalization of disease, procedure, and symptom mentions to SNOMED-CT/UMLS codes.
- Domain: Spanish biomedical/clinical texts.
- Corpora: DisTEMIST, MedProcNER, SympTEMIST.

---

## Benchmark Results

| Corpus      | Top-1  | Top-5  | Top-25 | Top-200 |
|-------------|--------|--------|--------|---------|
| DisTEMIST   | 0.588  | 0.723  | 0.803  | 0.867   |
| SympTEMIST  | 0.635  | 0.784  | 0.882  | 0.946   |
| MedProcNER  | 0.651  | 0.765  | 0.838  | 0.892   |