Artificial intelligence for the evaluation of profiles, trajectories and management of vulnerability in health: COVID-19, frailty of the elderly and cancer
ARAMIS (Project-Team)
Algorithms, models and methods for images and signals of the healthy and pathological human brain
Underway
Collaboration type
Research structure
Main objectives
ARAMIS is a joint research project-team of the Brain Institute (ICM), CNRS, Inria, Inserm and Sorbonne University.
ARAMIS is composed of researchers, hospital-universities and teacher-researchers from Inria, Inserm, Sorbonne University, CNRS, and AP-HP.
The ARAMIS team is dedicated to the design of computational, mathematical and statistical approaches for the analysis of multimodal data from patients with brain diseases, with a focus on neuroimaging data. The main methodological areas of our team are: machine learning, statistical modeling of complex geometric data, connectivity and network analysis. These new approaches are applied to clinical research in neurological diseases in collaboration with other teams of the ICM, clinical services of the Pitié-Salpêtrière hospital and other hospitals of the AP-HP, and external partners. The team has a multidisciplinary composition, bringing together researchers in mathematics, computer science and engineering (N. Burgos, O. Colliot, B. Couvy-Duchesne, F. De Vico Fallani, S. Durrleman, D. Racoceanu) and clinicians (D. Dormont, S. Tezenas du Montcel)
We are developing various clinical applications of our research, in particular in neurodegenerative diseases (Alzheimer's disease and other dementias, Parkinson's disease), multiple sclerosis, developmental disorders, strokes and to design brain-machine interfaces for rehabilitation.
ARAMIS is composed of researchers, hospital-universities and teacher-researchers from Inria, Inserm, Sorbonne University, CNRS, and AP-HP.
The ARAMIS team is dedicated to the design of computational, mathematical and statistical approaches for the analysis of multimodal data from patients with brain diseases, with a focus on neuroimaging data. The main methodological areas of our team are: machine learning, statistical modeling of complex geometric data, connectivity and network analysis. These new approaches are applied to clinical research in neurological diseases in collaboration with other teams of the ICM, clinical services of the Pitié-Salpêtrière hospital and other hospitals of the AP-HP, and external partners. The team has a multidisciplinary composition, bringing together researchers in mathematics, computer science and engineering (N. Burgos, O. Colliot, B. Couvy-Duchesne, F. De Vico Fallani, S. Durrleman, D. Racoceanu) and clinicians (D. Dormont, S. Tezenas du Montcel)
We are developing various clinical applications of our research, in particular in neurodegenerative diseases (Alzheimer's disease and other dementias, Parkinson's disease), multiple sclerosis, developmental disorders, strokes and to design brain-machine interfaces for rehabilitation.
Members
ICM, Inria, CNRS, Inserm, Sorbonne Université
Useful links
https://www.inria.fr/fr/aramis
Other projects
Description
Learning a deep representation of patient records for event prediction and patient segmentation
Names of partners involved
AP-HP, Inria