APPRIMAGE

Large-scale validation of a machine learning method for diagnostic support from brain MRI data
Underway
01/11/2018

Main objectives

The ARAMIS team is developing machine learning algorithms to help diagnose neurological diseases from brain magnetic resonance imaging data.
The present study aims to:
i) evaluate these algorithms on a very large scale on routine clinical data;
ii) evaluate the influence of the training sample size on the performance of the algorithms;
iii) compare different machine learning approaches.
Acquisition d'images cérébrales (IRM) - © Inria / Photo C. Morel

Publications

Members

Equipe-projet ARAMIS, Inria, CNRS, Inserm, Sorbonne Université, Institut du Cerveau Service de neuroradiologie diagnostique et fonctionnelle, DMU DIAMENT, Hôpital de la Pitié-Salpêtrière, AP-HP. Service de neurologie, IM2A, DMU Neurosciences, Hôpital de la Pitié-Salpêtrière, AP-HP.

Other projects

COVIPREDS

Description

US Caractérisation et prédiction de la survenue de formes graves ou létales du COVID-19 à partir des données issues de l’EDS de l’AP-HP

Names of partners involved
AP-HP, Inria & Centrale Supélec

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