Posos/MedNERF

Dataset

MedNERF

4

3 commits

1 linked in READMEs

updated Jun 7, 2023

See the code

README

MedNERF

Dataset Description

Dataset Summary

MedNERF is a French medical NER dataset whose aim is to serve as a test set for medical NER models. It has been built using a sample of French medical prescriptions annotated with the same guidelines as the n2c2 dataset. Entities are annotated with the following labels: Drug, Strength, Form, Dosage, Duration and Frequency, using the IOB format.

Licensing Information

This dataset is distributed under the Creative Commons Attribution Non Commercial Share Alike 4.0 license.

Citation information

@inproceedings{mednerf,
    title = "Multilingual Clinical NER: Translation or Cross-lingual Transfer?",
    author = "Gaschi, Félix and Fontaine, Xavier and Rastin, Parisa and Toussaint, Yannick",
    booktitle = "Proceedings of the 5th Clinical Natural Language Processing Workshop",
    publisher = "Association for Computational Linguistics",
    year = "2023"
}
medical

Posos/MedNERF

Dataset

MedNERF

4

3 commits

1 linked in READMEs

updated Jun 7, 2023

See the code

README

MedNERF

Dataset Description

Dataset Summary

MedNERF is a French medical NER dataset whose aim is to serve as a test set for medical NER models. It has been built using a sample of French medical prescriptions annotated with the same guidelines as the n2c2 dataset. Entities are annotated with the following labels: Drug, Strength, Form, Dosage, Duration and Frequency, using the IOB format.

Licensing Information

This dataset is distributed under the Creative Commons Attribution Non Commercial Share Alike 4.0 license.

Citation information

@inproceedings{mednerf,
    title = "Multilingual Clinical NER: Translation or Cross-lingual Transfer?",
    author = "Gaschi, Félix and Fontaine, Xavier and Rastin, Parisa and Toussaint, Yannick",
    booktitle = "Proceedings of the 5th Clinical Natural Language Processing Workshop",
    publisher = "Association for Computational Linguistics",
    year = "2023"
}
medical