Modelpublic

DT4H/es-procedure-cardioberta-multiclass-ner

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Model Card for Es-Procedure-Cardioberta-Multiclass

Description

Spanish clinical NER model for procedure recognition

Model Details

—Language: ES
—Task: token-classification
—Framework: pytorch

How to Use

python

from transformers import AutoTokenizer, AutoModelForTokenClassification

model_name = "DT4H/es-procedure-cardioberta-multiclass-ner"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForTokenClassification.from_pretrained(model_name)

Citation

bibtex

@inproceedings{danu2026siemens,
  title={SIEMENS at\# SMM4H--HeaRD 2026: The Impact of Training Strategy and Backbone Selection on BERT-based Multilingual Clinical NER},
  author={Danu, Manuela Daniela},
  booktitle={Proceedings of the 11th Social Media Mining for Health Research and Applications (SMM4H-HeaRD 2026) Workshop and Shared Tasks},
  pages={216--221},
  year={2026}
}

Acknowledgments

This work received funding from the European Union’s Horizon Europe research and innovation programme under Grant Agreement No. 101057849 (DataTools4Heart project).