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David Rodriguez Luna

Institutions of which they are part

Main researcher
Stroke research
Vall Hebron Institut de Recerca

David Rodriguez Luna

Institutions of which they are part

Main researcher
Stroke research
Vall Hebron Institut de Recerca

Projects

TRUSTroke: TRUSTWORTHY PREDICTION OF STROKE OUTCOME ON A FEDERATED LEARNING INFRASTRUCTURE

IP: Carlos Molina Cateriano
Collaborators: Estela Sanjuan Menendez, Laura Rivera Sanchez, Federica Rizzo, Marta Aurora Rubiera Del Fueyo, David Rodriguez Luna, Maria del Pilar Saez Hernandez, Maria Baladas Orti, Cristina Guirao Martinez
Funding agency: EUROPEAN COMMISSION
Funding: 760000
Reference: TRUSTROKE_HE-HLTH-STAYHLTH2022
Duration: 01/05/2023 - 30/04/2027

Monitorización hemodinámica de la hemorragia intracerebral

IP: David Rodriguez Luna
Collaborators: -
Funding agency: Instituto de Salud Carlos III
Funding: 60000
Reference: INT21/00015
Duration: 01/01/2022 - 31/12/2023

RES-Q PLUS: Comprehensive solutions of healthcare improvement based on the global Registry of Stroke Care Quality

IP: Carlos Molina Cateriano
Collaborators: Noelia Rodríguez Villatoro, Federica Rizzo, David Rodriguez Luna, Carole Conforti
Funding agency: EUROPEAN COMMISSION
Funding: 396730
Reference: RES-Q PLUS_HE-HLTH-TOOL21
Duration: 01/11/2022 - 31/10/2026

VALIDATE: Validation of a Trustworthy AI-based Clinical Decision Support System for Improving Patient Outcome in Acute Stroke Treatment

IP: Marta Aurora Rubiera Del Fueyo
Collaborators: Maria Victoria Sala Sanz de Madrid, Cristina Guirao Martinez, Claudia Meza Burgos, Federica Rizzo, Ester Sanchez Gavilan, David Rodriguez Luna
Funding agency: EUROPEAN COMMISSION
Funding: 567950
Reference: VALIDATE_HE-HLTH-DISEASE21
Duration: 01/05/2022 - 30/04/2026

Related news

The Stroke Research and the Neurovascular Diseases groups lead innovative research projects in both clinical and translational areas.

The team will develop a new medical tool to facilitate the removal of blood clots in blood vessels after a stroke in a safer and more effective manner.

A retrospective study has been carried out with data from 11,000 patients to train artificial intelligence algorithms and adapt the Nora mobile application to different patient profiles.

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