MediCIS

Models of Surgical and Interventional Competencies

Modélisation des compétences chirurgicales et interventionnelles

Team Coordinator: Pierre Jannin

MediCIS is a INSERM research team of the UMR Inserm U1099 LTSI from University of Rennes, affiliated to INSERM (National Institute of Health and Scientific Research) and is located in Rennes, France at the Medical University.

The MediCIS team’s project aims at improving surgical quality by means of Surgical Data Science for both surgical performance and training. Surgical data science has the potential to revolutionize surgery. Relying upon recent progress in artificial intelligence (AI) and deep learning, surgical data science aims to rely on data collected all along the surgical process, being analyzed to produce explicit knowledge that can be used for decision support, evaluation or training. Following our pioneered research on surgical process modeling and analysis, surgical data science includes analysis of human and effectors processes in addition to patient data. An holistic analysis of the surgical environment is then used for developing the next generation of computer assisted surgical systems and surgical simulators.

Main Research Projects

SPARS: Sequential Pattern Analysis in Robotic Surgery: Understanding Surgery (PI-3 years) Funding from LabEx CominLabs
AIR-Medical: VR for NTS (PI-3 years) Funding from PIA4
M-DBS: « Model Guided Deep Brain Stimulation : Understanding of underlying phenomenon and improvement of surgical procedure » (PI-4 years) Funding from INCR
« Surgical Data Science for Improving Quality » (PI-4 years) Funding from ANR-PRCI

Past Research Projects

MediCIS News

04/04/2024: Call of paper for the Hamlyn Workshop “Applying Surgical Data Science in Robotic Surgery” that we co-organized the 25th June 2024
04/11/2023: Nous co-organisons le workshop XR4MedSIM: La Simulation par Réalité Virtuelle pour Apprendre les Facteurs Humains en Santé: est ce pertinent ? 11/01/2024
04/10/2023: Le Pélerin Magazine a récemment consacré un article complet à nos travaux sur la réalité virtuelle

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Involvement in Conferences

Call of paper for the Hamlyn Workshop “Applying Surgical Data Science in Robotic Surgery” that we co-organized the 25th June 2024
Nous organisons le workshop XR4MedSIM: La Simulation par Réalité Virtuelle pour Apprendre les Facteurs Humains en Santé: est ce pertinent ? Rennes, le 11/01/2024
We are involved in the organization of ISBI international conference in 2023.
Organization of CARS 2019 CONFERENCE in RENNES June 17-21 2019...

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Facts

Between 6 and 8 millions of surgical procedures per year in France (250 millions worldwide)
More patients in an older population need for more surgical procedures with better health care
10 000 to 15 000 avoidable serious adverse events occur in the peri-operative process per year in France

Global Vision

Improving surgical quality by means of:

Surgical decision support with predictive models of best practice
Evaluation and training of both technical and non-technical surgical skills

Methods:

Surgical Data Science
Artificial Intelligence and Machine Learning
Study and understanding of surgical competencies within simulated and real clinical environments
Study of methods for modeling and evaluation of competencies from observed data
Implementation of models and methods within systems allowing evaluating, ensuring and/or optimising surgical quality

Our core competencies: Surgical Data Science, Artificial Intelligence and Machine Learning, Data fusion and image processing, Ontologies

For more details about the methodological and applicative objectives on these issues, go to the Scientific Activities page.