MAESTRIA – Machine Learning and Artificial Intelligence for Early Detection of Stroke and Atrial Fibrillation

H2020 SC1-BHC-06-2020 call on digital diagnostics

The project aims to develop and validate the first integrative diagnostic digital platform for atrial cardiomyopathy diagnosis. This platform will be designed to provide support for improved diagnostic accuracy that increases effectiveness and efficiency of treatments, as well as prevention of the complications of atrial cardiomyopathy, such as atrial fibrillation and stroke.

Coordinator
Stéphane Hatem and Sorbonne University

Partners
ASSISTANCE PUBLIQUE HOPITAUX DE PARIS – Pr RICHARD ISNARD
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD – Pr CHARALAMBOS ANTONIADES
THE UNIVERSITY OF BIRMINGHAM – Dr LARISSA FABRITZ
AFNET – Dr ANDREAS GOETTE
UNIVERSITAETSKLINIKUM ESSEN – Pr DOBROMIR DOBREV
UNIVERSITEIT MAASTRICHT – Pr ULRICH SCHOTTEN
The National and Kapodistrian University of Athens – DIMITRIS TOUSOLIS
CENTRO NACIONAL DE INVESTIGACIONESCARDIOVASCULARES CARLOS III – JOSE JALIFE
THE GENERAL HOSPITAL CORPORATION – Patrick Thomas ELLINOR
IMT TRANSFERT – Anne-Sophie TAILLANDIER
Centre de recherche du CHUS – ANDRE CARPENTIER
SIEMENS HEALTHCARE GMBH – TOBIAS HEIMANN / CHLOE AUDIGIER
Caristo Diagnostics Limited – DAN GREEN
OWKIN France – GILLES WAINRIB
IDOVEN 1903, S.L – MANUEL MARINA BREYSSE
PREVENTICUS GMBH – THOMAS HÜBNER
YourRhythmics – PATRIC MACHIELS

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