metadata

license: apache-2.0
task_categories:
  - text-classification
language:
  - fr
tags:
  - medical
  - biology
pretty_name: MORFITT
size_categories:
  - 1K<n<10K

MORFITT

Data (Zenodo) | Publication (HAL)

Yanis LABRAK, Richard DUFOUR, Mickaël ROUVIER

We introduce MORFITT, the first multi-label corpus for the classification of specialties in the medical field, in French. MORFITT is composed of 3,624 summaries of scientific articles from PubMed, annotated in 12 specialties. The article details the corpus, the experiments and the preliminary results obtained using a classifier based on the pre-trained language model CamemBERT.

For more details, please refer to our paper:

MORFITT: A multi-label topic classification for French Biomedical literature (HAL)

Key Features

Documents distribution

Train	Dev	Test
1,514	1,022	1,088

Multi-label distribution

	Train	Dev	Test	Total
Vétérinaire	320	250	254	824
Étiologie	317	202	222	741
Psychologie	255	175	179	609
Chirurgie	223	169	157	549
Génétique	207	139	159	505
Physiologie	217	125	148	490
Pharmacologie	112	84	103	299
Microbiologie	115	72	86	273
Immunologie	106	86	70	262
Chimie	94	53	65	212
Virologie	76	57	67	200
Parasitologie	68	34	50	152
Total	2,110	1,446	1,560	5,116

Number of labels per document distribution

drawing

Co-occurences distribution

drawing

If you use HuggingFace Transformers

from datasets import load_dataset
dataset = load_dataset("qanastek/MORFITT")
print(dataset)

from datasets import load_dataset
dataset_base = load_dataset(
    'csv',
    data_files={
        'train': f"./train.tsv",
        'validation': f"./dev.tsv",
        'test': f"./test.tsv",
    },
    delimiter="\t",
)

License and Citation

The code is under Apache-2.0 License.

The MORFITT dataset is licensed under Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). If you find this project useful in your research, please cite the following papers:

Labrak, Y., Rouvier, M., & Dufour, R. (2023). MORFITT : Un corpus multi-labels d’articles scientifiques français dans le domaine biomédical. In F. Boudin, B. Daille, R. Dufour, O. Khettari, M. Houbre, L. Jourdan, & N. Kooli (Eds.), 18e Conférence en Recherche d’Information et Applications – 16e Rencontres Jeunes Chercheurs en RI – 30e Conférence sur le Traitement Automatique des Langues Naturelles – 25e Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (pp. 66–70). ATALA. https://hal.science/hal-04131591

or using the bibtex:

@inproceedings{labrak:hal-04131591,
  TITLE = {{MORFITT : Un corpus multi-labels d'articles scientifiques fran{\c c}ais dans le domaine biom{\'e}dical}},
  AUTHOR = {Labrak, Yanis and Rouvier, Mickael and Dufour, Richard},
  URL = {https://hal.science/hal-04131591},
  BOOKTITLE = {{18e Conf{\'e}rence en Recherche d'Information et Applications -- 16e Rencontres Jeunes Chercheurs en RI -- 30e Conf{\'e}rence sur le Traitement Automatique des Langues Naturelles -- 25e Rencontre des {\'E}tudiants Chercheurs en Informatique pour le Traitement Automatique des Langues}},
  ADDRESS = {Paris, France},
  EDITOR = {Boudin, Florian and Daille, B{\'e}atrice and Dufour, Richard and Khettari, Oumaima and Houbre, Ma{\"e}l and Jourdan, L{\'e}ane and Kooli, Nihel},
  PUBLISHER = {{ATALA}},
  PAGES = {66-70},
  YEAR = {2023},
  KEYWORDS = {Analyse de documents scientifiques ; Jeux de donn{\'e}es compos{\'e}s des textes scientifiques},
  PDF = {https://hal.science/hal-04131591/file/1465546.pdf},
  HAL_ID = {hal-04131591},
  HAL_VERSION = {v1},
}