Artificial intelligence for the evaluation of profiles, trajectories and management of vulnerability in health: COVID-19, frailty of the elderly and cancer
MOSAIC (University Hospital Federation)
(Multiscale Optimised Strategy for Artificial intelligence-based Imaging biomarkers in digestive Cancer)
Underway
12/10/2020
-
10/10/2025
Collaboration type
Research structure
Main objectives
MOSAIC aims to identify prognostic and theranostic biomarkers of digestive tumors through the development of a multi-parametric multi-scale imaging approach, combining radiology (macroscopy), pathology (microscopy and molecular) and nuclear medicine (functional): IMAGOMICS. Using Artificial Intelligence (AI) methods, this project mixes the multiple facets of tumor imaging to improve tumor characterization and disease monitoring. In particular, it will allow us to highlight correlations between histology, imaging markers and tumor aggressiveness/response to therapy that remain hidden until now. Thus, we will propose non-invasive diagnostic, prognostic and theranostic modalities through virtual biopsy.
The project will focus on two types of digestive tumors: hepatocellular carcinomas (HCC) and neuroendocrine tumors (NET).
The project will focus on two types of digestive tumors: hepatocellular carcinomas (HCC) and neuroendocrine tumors (NET).

Contacts
Valérie Paradis () & Kevin Mondet ()
Members
AP-HP, Inserm, Université Paris Cité
Useful links
https://fhu-mosaic.com/
Other projects
Description
Learning a deep representation of patient records for event prediction and patient segmentation
Names of partners involved
AP-HP, Inria