Artificial intelligence for the evaluation of profiles, trajectories and management of vulnerability in health: COVID-19, frailty of the elderly and cancer
R2D2
US from clinical Records 2 Diagnostic Decisions
Underway
01/12/2021
-
30/12/2021
Collaboration type
Project
Main objectives
The R2D2 project proposes to study how formal or semi-formal representations of clinical protocols for diagnosis can be automatically learned from patient data. To this end, we (1) study two families of methods to infer such decision processes from clinical data warehouses, and (2) will define a framework for evaluating and comparing learned and pre-existing protocols.
Contacts:
Antoine Neuraz, antoine.neuraz@aphp.fr, HeKA team and Necker Hospital, AP-HP
Adrien Coulet, adrien.coulet@inria.fr, HeKA team
Contacts:
Antoine Neuraz, antoine.neuraz@aphp.fr, HeKA team and Necker Hospital, AP-HP
Adrien Coulet, adrien.coulet@inria.fr, HeKA team

© Inria / Photo H. Raguet
Members
AP-HP, Inria, Inserm, Université de Paris
Other projects
Description
Learning a deep representation of patient records for event prediction and patient segmentation
Names of partners involved
AP-HP, Inria