TRUSTroke: TRUSTWORTHY AI FOR IMPROVEMENT OF STROKE OUTCOMES

TRUSTroke proposes a novel trustworthy by design and privacy-preserving AI-based platform to assist clinicians, patients and caregivers in the management of acute and chronic phases of ischemic stroke, based on the integration of clinical and patient-reported data for a trustworthy assessment of disease progression, specifically related to risks of (i) clinical severity at discharge (ii) clinical worsening leading to unplanned hospital readmissions, (iii) poor mobility, incomplete recovery and unfavourable clinical long-term outcomes (iv) stroke recurrence. A Federated Learning (FL) infrastructure (hosted by CERN) will be developed and used to enable multiple clinical sites to collaboratively build several trustworthy AI based predictive models by leveraging stroke data without compromising privacy and implementing best-in-class security protocols, easing compliance with GDPR and lowering adoption barriers by hospitals.

Coordinator: FUNDACIO HOSPITAL UNIVERSITARI VALL D'HEBRON - INSTITUT DE RECERCA

Scientist in Charge from CERN: Luigi SERIO

EU funding: € 6 076 437,50

EU funding for CERN: € 1 018 500.00

Date: 01/05/2023 - 30/04/2027