metadata
language: multilingual
task_ids:
- token-classification
tags:
- clinical, medical, ner, healthcare
Model Card for Multilingual-Symptom-Xlm-Roberta-Large-Multiclass
Description
Multilingual clinical NER model for symptom recognition
Model Details
- Language: MULTILINGUAL
- Task: token-classification
- Framework: pytorch
How to Use
from transformers import AutoTokenizer, AutoModelForTokenClassification
model_name = "DT4H/multilingual-symptom-xlm-roberta-large-multiclass-ner"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForTokenClassification.from_pretrained(model_name)
Citation
@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).