Axis 5: Health

The health and social protection systems in France and in Europe involve numerous actors: hospitals, social services, companies, universities and research and regulation centers. Data is collected from multiple sources, and while personalised patient information can revolutionize diagnosis and treatment, the real problem is capturing, storing, and understanding it. With AI, health becomes smart health, making true the promises of the P4 (Predictive, Personalized, Preemptive, Participative) vision of medicine. The CHU of Grenoble possesses both the data acquisition tools (a data lake that will be part of the French hub for AI in Health, clinical metabolomics platform) and the environment to develop and test AI-based devices (it hosts one of the 8 French Centers for Clinical Investigation and Technological Innovation). Furthermore, Grenoble is a major place of AI technologies for health, thanks to its interdisciplinary skills and its long-standing cooperation between physicians, mathematicians, computer scientists, chemists and industrial actors. Our strategy within MIAI is to enlarge these perspectives through a continuous effort on data collection and the development of new AI-based tools for omics, improved health trajectories, improved computerized assistants and augmented patient empowerment. The three programs below address some of these issues.

5.1. Real-life 4P medecine

This program aims at demonstrating the relevance of new AI tools to facilitate the empowerment of citizens by exploring new challenges related to smart data capture, smart data fusion and new approaches for decision-making. A specific case study will be conducted on a major health challenge, the Obstructive Sleep Apnea (OSA), affecting over billion people worldwide.

  • Deep Care: Patient Empowerment via a Participatory Health Project - Philippe Cinquin
  • My Way to Health “trajectories medicine” - Emmanuel Mignot (International) & Jean-Louis Pépin (Local)

5.2. Multiomics

Following our perspectives of developing new AIbased tools for “omics”, a dedicated AI program will focus on the identification of new biomarkers from multimodal health data and on the development of new tools to compute personalised risk scores, potentially leading to new medical practices.

  • Artificial Intelligence for High throughput biomedical investigations - Thomas Burger (AI) & Julien Thévenon (Medicine)

Computer-asssisted medical intelligence

Finally, a dedicated program will focus on the development of new generation of intra-operative AI-based computerised assistants with the will to treat patients more efficiently and less invasively. The ability to explain the decisions made by the assistants as well as the guarantee of safety and clinical efficiency will drive this development.
  • Computer-Assisted Medical Interventions (CAMI) Assistant - Jocelyne Troccaz & Sandrine Voros