Bilateral Contracts and Grants with Industry
Bilateral Contracts and Grants with Industry

Section: Partnerships and Cooperations

National Initiatives


#DigitAg: Digital agriculture

Participants : Alexandre Termier, Véronique Masson, Christine Largouët, Anne-Isabelle Graux.

#DigitAg is a “Convergence Institute” dedicated to the increasing importance of digital techniques in agriculture. Its goal is twofold: First, make innovative research on the use of digital techniques in agriculture in order to improve competitiveness, preserve the environment, and offer correct living conditions to farmers. Second, prepare future farmers and agricultural policy makers to successfully exploit such technologies.

While #DigitAg is based on Montpellier, Rennes is a satellite of the institute focused on cattle farming. LACODAM is involved in the “data mining” challenge of the institute, that A. Termier co-leads. He is also the representative of Inria in the steering comittee of the institute.

The interest for the team is to design novel methods to analyze and represent agricultural data, which are challenging because they are both heterogeneous and multi-scale (both spatial and temporal).

National Platforms

PEPS : Pharmaco-epidemiology for Health Products

Participants : Yann Dauxais, Thomas Guyet, Véronique Masson, René Quiniou, Ahmed Samet.

The PEPS project (Pharmaco-epidemiology des Produits de Santé) is funded by the ANSM (National Agency for Health Security). The project leader is E. Oger from the clinical investigation center CIC-1414 INSERM/CHU Rennes. The other partners located in Rennes are the Institute of Research and Technology (IRT), B<>Com, EHESP and the LTSI. The project started in January 2015 and is funded for 4 years.

The PEPS project consists of two parts: a set of clinical studies and a research program dedicated to the development of innovative tools for pharmaco-epidemiological studies with medico-administrative databases.

Our contribution to this project will be to propose pattern mining algorithms and reasoning techniques to analyse the typical care pathways of specific groups of insured patients. This year we worked on the design and development of the DCM algorithm [8], [7] to mine patterns on care pathways.