The MAESTRIA (Machine Learning and Artificial intelligence for Early detection of Stroke and Atrial Fibrillation) project is an 18-partner Research and Innovation action that answers the H2020 SC1-BHC-06-2020 call on digital diagnostics – developing tools for supporting clinical decisions by integrating various diagnostic data. Coordinated by Sorbonne University (PI: Stéphane Hatem), the project also involves 17 other European partners, including SCAI.
The acronym is used by the MAESTRIA consortium as a metaphor for expressing the mastery that leads to complete control of personalised and early diagnosis of atrial fibrillation and cardioembolic stroke, two major health problems.
The MAESTRIA project focuses on developing novel approaches for timely detection of atrial myopathy to improve care management and identifying novel therapeutic targets for personalised medicine of atrial fibrillation and stroke.
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.