ORD-IA
Optimizing the Reuse of Health Data Through Artificial Intelligence – Application to Medical Image Analysis in Orthopedic Surgery
Orthopedic surgery represents a major public health challenge, particularly because of fractures resulting from accidents, population aging, and osteoporosis, as well as degenerative musculoskeletal conditions such as osteoarthritis. Clinical care and research in this field rely heavily on the analysis of medical imaging data. However, the secondary use of these images for research purposes remains complex.
In this context, the ORD-IA project aims to develop a proof-of-concept artificial intelligence (AI) algorithm capable of automatically identifying healthy and pathological bone structures—including fractures and osteoarthritis—from 3D computed tomography (CT) images. The objective is to automate the identification and selection of relevant imaging data, thereby facilitating the creation of reliable, research-ready imaging databases for orthopedic and trauma research.
Ultimately, ORD-IA aims to improve the quality and accessibility of medical imaging data, accelerate the development of research cohorts, and support the development of future tools for diagnostic and clinical decision support.
Project Leader
Marc-Olivier Gauci, University Professor and Hospital Practitioner (Orthopedic Surgeon), Principal Investigator of the ICARE Team, Nice University Hospital (CHUN), and Administrator of GCS CARES.Project Team
- Dr. Abdelbasset Brahim. Senior Expert in AI Applied to Medicine, ICARE Team
- Dr. Stéphanie Lopez. Senior Engineer, MSI – Center of Modeling, Simulation and Interactions, Université Côte d’Azur.
Partners
- GCS CARES (Healthcare Research and Excellence Consortium).
- Medexprim.