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 (2024)

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.

## labels to assess the model's performance for each label individually, we used the confusion matrix on the predictive accuracy of camembert-base-weighted (see figure 5 ). the matrix layout consists of rows representing true labels and columns representing predicted labels. high values along the diagonal indicate the model's proficiency in making accurate predictions. by examining the matrix, we can observe that the affection_sein (breast disorders) category has yielded the highest number of accurate predictions. this can be attributed to the relatively independent nature of breast disorders within the domain of women's intimate health, where questions of this category are less related to other topics. additionally, there is some confusion between fertilité (fertility) and conception (conception), two closely related concepts. it can be difficult even for humans to clearly distinguish them apart.