# Building Commons for Clinical LLMs

**URL:** https://entraide.health-data-hub.fr/t/building-commons-for-clinical-llms/3324
**Category:** Annonces
**Created:** [Juillet 3, 2026, 3:16 UTC](https://entraide.health-data-hub.fr/t/building-commons-for-clinical-llms/3324 "2026-07-03T15:16:47Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![Yasmine\_Harim](https://entraide.health-data-hub.fr/letter_avatar_proxy/v4/letter/y/50afbb/32.png) [@Yasmine\_Harim](https://entraide.health-data-hub.fr/u/Yasmine_Harim)
#### Post date: [Juillet 3, 2026, 3:16 UTC](https://entraide.health-data-hub.fr/t/building-commons-for-clinical-llms/3324/1 "2026-07-03T15:16:47Z")

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![Building commons _ bandeau mail invitation](https://entraide.health-data-hub.fr/uploads/default/original/1X/71fe7f162fc3ef890c8da3d7711a7fc2d15d0798.png)

While **Large Language Models (LLMs)** offer transformative potential for healthcare professionals, their development is subject to strict regulatory frameworks governing clinical data access.

Beyond this hurdle, most generic models lack the deep domain expertise required for clinical accuracy, a limitation that is even more pronounced in non-English speaking environments. Furthermore, given the non-deterministic nature of LLMs, their use in a medical context presents inherent patient safety risks. This necessitates absolute precision and the establishment of standardized clinical benchmarks to rigorously evaluate model performance across diverse medical specialties.

This conference aims to:

- **Present recent research and findings on LLMs in healthcare** , with a particular focus on open-source and collaborative approaches.

- **Foster discussion & collaboration** on the major regulatory, scientific, technical and ethical challenges associated with LLMs in healthcare.

- **Open a dialogue with industry stakeholders** to compare research findings with real-world applications, limitations, and the conditions for deployment.

- **Address the associated regulatory and ethical challenges** , in relation to existing and emerging frameworks, and their impact.

What to Expect:

- **120 participants** : researchers, healthcare & industry professionals

- Day 1 (October 1st) : **6 keynote spotlights** , **2 high-level panel sessions** and dedicated poster & networking sessions

- Day 2 (October 2nd): **3 collaborative workshops**

The conference will feature an international lineup of speakers pushing the frontiers of the use and challenges of LLMs in healthcare. Detailed schedule coming soon!  
**[Check out the event flyer](https://health-data-hub.fr/sites/default/files/2026-06/Flyer%20Building%20commons%20for%20clinical%20LLMs%20%282%29.pdf)**

**October 1 & 2, 2026, Paris (France)**  
_**[Fill out this form to pre-register](https://hdhpds.limesurvey.net/911354)**_  
_A confirmation email regarding your registration status will be sent by the organizing committee._

This conference is organized by :  
**- French Health Data Hub** (Plateforme des données de santé)  
**- LISN** (Interdisciplinary Laboratory of Numerical Sciences - **CNRS** , Université Paris-Saclay, Inria, CentraleSupelec)  
**- LIMICS** (Laboratory for research in health informatics - Inserm, Sorbonne Université, Université Sorbonne Paris Nord)  
**- LIG** (Computer Science Laboratory of Grenoble - CNRS, Grenoble INP, Inria, Université Grenoble Alpes)  
The event is supported by **DIM AI4IDF**.

**First Confirmed Keynotes**  
We are thrilled to announce the topics and institutions for our first three keynotes:

- _Evaluation and implementation of LLMs for medical tasks_ – Stanford Medicine (USA)

- _Development and evaluation of a Japanese Medical LLM_ – RIKEN iTHEMS (Japan)

- _Development of open-source digital commons (models, data, tools) for generative AI in healthcare and in French_ - PARTAGES Consortium (France)

More keynote and the full detailed schedule will be announced very soon! Stay tuned.