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README.md
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## Model Description
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ClinLinker-KB-GP is a state-of-the-art bi-encoder model for medical entity linking (MEL) in Spanish, optimized for clinical domain tasks. It enriches concept representations by incorporating not only synonyms but also hierarchical relationships (parents and grandparents) from the UMLS and SNOMED-CT ontologies. The model was trained with a contrastive-learning strategy using hard negative mining and multi-similarity loss.
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## Intended Use
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- **Domain**: Spanish Clinical NLP
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- **Tasks**: Entity linking (diseases, symptoms, procedures) to SNOMED-CT
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- **Evaluated On**: DisTEMIST, MedProcNER, SympTEMIST
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*Results correspond to the cleaned gold-standard version (no "NO CODE" or "COMPOSITE").*
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## Usage
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```python
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from transformers import AutoModel, AutoTokenizer
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- The model is optimized for Spanish clinical data and may underperform outside this domain.
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- Expert validation is advised in critical applications.
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## Citation
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> Gallego, Fernando and L贸pez-Garc铆a, Guillermo and Gasco, Luis and Krallinger, Martin and Veredas, Francisco J., Clinlinker-Kb: Clinical Entity Linking in Spanish with Knowledge-Graph Enhanced Biencoders. Available at SSRN:http://dx.doi.org/10.2139/ssrn.4939986.
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## Model Description
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ClinLinker-KB-GP is a state-of-the-art bi-encoder model for medical entity linking (MEL) in Spanish, optimized for clinical domain tasks. It enriches concept representations by incorporating not only synonyms but also hierarchical relationships (parents and grandparents) from the UMLS and SNOMED-CT ontologies. The model was trained with a contrastive-learning strategy using hard negative mining and multi-similarity loss.
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## 馃挕 Intended Use
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- **Domain**: Spanish Clinical NLP
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- **Tasks**: Entity linking (diseases, symptoms, procedures) to SNOMED-CT
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- **Evaluated On**: DisTEMIST, MedProcNER, SympTEMIST
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*Results correspond to the cleaned gold-standard version (no "NO CODE" or "COMPOSITE").*
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## 馃И Usage
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```python
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from transformers import AutoModel, AutoTokenizer
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- The model is optimized for Spanish clinical data and may underperform outside this domain.
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- Expert validation is advised in critical applications.
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## 馃摎 Citation
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> Gallego, Fernando and L贸pez-Garc铆a, Guillermo and Gasco, Luis and Krallinger, Martin and Veredas, Francisco J., Clinlinker-Kb: Clinical Entity Linking in Spanish with Knowledge-Graph Enhanced Biencoders. Available at SSRN:http://dx.doi.org/10.2139/ssrn.4939986.
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