@inproceedings{liu-etal-2024-meddialog,
    title = "{M}ed{D}ialog-{FR}: A {F}rench Version of the {M}ed{D}ialog Corpus for Multi-label Classification and Response Generation Related to Women{'}s Intimate Health",
    author = "Liu, Xingyu  and
      Segonne, Vincent  and
      Mannion, Aidan  and
      Schwab, Didier  and
      Goeuriot, Lorraine  and
      Portet, Fran{\c{c}}ois",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Thompson, Paul  and
      Ondov, Brian",
    booktitle = "Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.cl4health-1.21",
    pages = "173--183",
    abstract = "This article presents MedDialog-FR, a large publicly available corpus of French medical conversations for the medical domain. Motivated by the lack of French dialogue corpora for data-driven dialogue systems and the paucity of available information related to women{'}s intimate health, we introduce an annotated corpus of question-and-answer dialogues between a real patient and a real doctor concerning women{'}s intimate health. The corpus is composed of about 20,000 dialogues automatically translated from the English version of MedDialog-EN. The corpus test set is composed of 1,400 dialogues that have been manually post-edited and annotated with 22 categories from the UMLS ontology. We also fine-tuned state-of-the-art reference models to automatically perform multi-label classification and response generation to give an initial performance benchmark and highlight the difficulty of the tasks.",
}

This article presents MedDialog-FR, a large publicly available corpus of French medical conversations for the medical domain. Motivated by the lack of French dialogue corpora for data-driven dialogue systems and the paucity of available information related to women{'}s intimate health, we introduce an annotated corpus of question-and-answer dialogues between a real patient and a real doctor concerning women{'}s intimate health. The corpus is composed of about 20,000 dialogues automatically translated from the English version of MedDialog-EN. The corpus test set is composed of 1,400 dialogues that have been manually post-edited and annotated with 22 categories from the UMLS ontology. We also fine-tuned state-of-the-art reference models to automatically perform multi-label classification and response generation to give an initial performance benchmark and highlight the difficulty of the tasks.
Liu, Xingyu Segonne, Vincent Mannion, Aidan Schwab, Didier Goeuriot, Lorraine Portet, Fran{\c{c}}ois
MedDialog-FR: A French Version of the MedDialog Corpus for Multi-label Classification and Response Generation Related to Women's Intimate Health