Grands modèles de langue adaptables et souverains pour le domaine médical français
The recent arrival of Large Language Models (LLMs) and their associated tools for the general public reveals major challenges for society. Among the many fields that are, or will be, impacted by these generative models, the biomedical field is one of those that currently attract the attention of industrialists, researchers, but also the general public. Indeed, the need for tools and potential applications seems immense, whether, for example, at the level of the processing of textual documents, medical imaging, or even voice interaction. Due to the sensitive nature of the personal data handled and the fears of society associated with decision support tools, work in natural language processing (NLP) must innovate by addressing the issues inherent in this field. As part of the MALADES project, we presented innovative approaches for the integration of LLM in health centers. The aim is to equip these centers with NLP tools derived from LLMs and adapted for the biomedical field while maintaining sovereignty of the models and complete control of their health data. The work we carry out focuses on four areas of research: 1) the study of the legal and ethical aspects in France of LLMs for the biomedical field, 2) the integration of an interaction by the speech of LLMs by means of end-to-end approaches, including the massive collection of speech data, 3) The collection of new original case studies oriented for the evaluation of generative language models, and 4) the integration of dynamic and sovereign LLMs for the biomedical field, deployed on constrained material resources, and integrating original approaches providing LLMs with additional capabilities by means of mastered and verified knowledge bases.
Liste des partenaires :
- LIA
- LIS
- LS2N
- CHUN
Responsable Scientifique pour le LIA : Mickael Rouvier
Date Début : 2023-10-01 Date Fin : 2027-10-01