BioLORD 2023 M Dutch InContext v1 EU AI Act Compliance Profile

In-Context Dutch Clinical Embeddings with BioLORD & MedMentions

Do mentions sharing the same text need to have the same embedding? No!

This model supports embedding biomedical entities in both English and Dutch, but allows the in-context embedding of concepts, using the following template:

It also supports embedding mentions without context, particularly in English.<br> NOTE: Unlike other models in the series, this model uses the [CLS] token to embed the mention.

References

📖 BioLORD-2023: semantic textual representations fusing large language models and clinical knowledge graph insights

Journal of the American Medical Informatics Association, 2024<br> François Remy, Kris Demuynck, Thomas Demeester<br> view online

📖 Annotation-preserving machine translation of English corpora to validate Dutch clinical concept extraction tools

Under review, with a preprint available on Medrxiv.org, 2024<br> Tom Seinen, Jan Kors, Erik van Mulligen, Peter Rijnbeek<br> view online

Citation

This model accompanies the BioLORD-2023: Learning Ontological Representations from Definitions paper. When you use this model, please cite the original paper as follows:

@article{remy-etal-2023-biolord,
    author = {Remy, François and Demuynck, Kris and Demeester, Thomas},
    title = "{BioLORD-2023: semantic textual representations fusing large language models and clinical knowledge graph insights}",
    journal = {Journal of the American Medical Informatics Association},
    pages = {ocae029},
    year = {2024},
    month = {02},
    issn = {1527-974X},
    doi = {10.1093/jamia/ocae029},
    url = {https://doi.org/10.1093/jamia/ocae02

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