Published May 10, 2024 | Version v3
Dataset Open

Multi-head CRF classifier for biomedical multi-class Named Entity Recognition on Spanish clinical notes

Authors/Creators

  • 1. ROR icon University of Aveiro

Description

This contains the merged dataset as described in the work "Multi-head CRF classifier for biomedical multi-class Named Entity Recognition on Spanish clinical notes".

This dataset consists of 4 seperate datasets:

The dataset contains two tasks:

Task 1: This task is related to multi-class Named Entity Recognition. This dataset contains 5 possible classes: SYMPTOM, PROCEDURE, DISEASE, CHEMICAL and PROTEIN.

Task 2: This task is related to Named Entity Linking, where each code corresponds to a code within the SNOMED-CT corpus. The exact corpus used can be obtained here. Further for the MedProcNER, SympTEMIST and DisTEMIST datasets, a gazetteer is provided in the original datasets. 

For more information on the construction of the dataset, aswell as dataloaders, we refer you to our GitHub repository.

Further this also contains the embeddings from the SapBERT model.

Please, cite:

@article{jonker2024a, title = {Multi-head {{CRF}} classifier for biomedical multi-class named entity recognition on {{Spanish}} clinical notes}, author = {Jonker, Richard A. A. and Almeida, Tiago and Antunes, Rui and Almeida, Jo{\~a}o R. and Matos, S{\'e}rgio}, year = {2024}, journal = {Database}, publisher = {Oxford University Press} }
Jonker, R. A. A., Almeida, T., Antunes, R., Almeida, J. R., & Matos, S. (2024). Multi-head CRF classifier for biomedical multi-class named entity recognition on Spanish clinical notes. (Submitted.) 
 

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Files

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Additional details

Dates

Submitted
2024-05-06

Software

Repository URL
https://github.com/ieeta-pt/Multi-Head-CRF
Programming language
Python
Development Status
Active

References

  • Miranda-Escalada, A., Gascó, L., Lima-López, S., Farré-Maduell, E., Estrada, D., Nentidis, A., Krithara, A., Katsimpras, G., Paliouras, G., & Krallinger, M. (2022). Overview of DisTEMIST at BioASQ: Automatic detection and normalization of diseases from clinical texts: results, methods, evaluation and multilingual resources. Working Notes of Conference and Labs of the Evaluation (CLEF) Forum. CEUR Workshop Proceedings
  • Lima-López S, Farré-Maduell E, Gascó L, Nentidis A, Krithara A, Katsimpras G, Paliouras G, Krallinger M. Overview of MedProcNER task on medical procedure detection and entity linking at BioASQ 2023. Working Notes of CLEF. 2023.
  • Lima-López, S., Farré-Maduell, E., Gasco-Sánchez, L., Rodríguez-Miret, J. and Krallinger, M. (2023). Overview of SympTEMIST at BioCreative VIII: corpus, guidelines and evaluation of systems for the detection and normalization of symptoms, signs and findings from text. In: Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models.
  • A. G. Agirre, M. Marimon, A. Intxaurrondo, O. Rabal, M. Villegas, M. Krallinger, Pharmaconer: Pharmacological substances, compounds and proteins named entity recognition track, in: Proceedings of The 5th Workshop on BioNLP Open Shared Tasks, 2019, pp. 1–10.