SECURED for Health: Scaling Up Privacy to Enable the Integration of the European Health Data Space.

Francesco Regazzoni,Gergely Ács, Albert Zoltan Aszalos, Christos Avgerinos, Nikolaos Bakalos,Josep Lluis Berral,Joppe W. Bos,Marco Brohet, Andrés G. Castillo Sanz, Gareth T. Davies, Stefanos Florescu, Pierre-Elisée Flory,Alberto Gutierrez-Torre,Evangelos Haleplidis,Alice Héliou, Sotirios Ioannidis, Alexander Islam El-Kady,Katarzyna Kapusta,Konstantina Karagianni,Pieter Kruizinga, Kyrian Maat, Zoltán Ádám Mann, Kalliopi Mastoraki, SeoJeong Moon, Maja Nisevic,Balázs Pejó,Kostas Papagiannopoulos,Vassilis Paliouras,Paolo Palmieri,Francesca Palumbo, Juan Carlos Pérez Baun, Péter Pollner, Eduard Porta-Pardo,Luca Pulina,Muhammad Ali Siddiqi, Daniela Spajic,Christos Strydis, Georgios Tasopoulos,Vincent Thouvenot,Christos Tselios,Apostolos P. Fournaris

Design, Automation, and Test in Europe（2024）

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摘要

In this paper, we present the SECURED project ¹ ¹ Funded in part by the European Union (EU), Grant Agreement no. 10109571. Views and opinions expressed are those of the authors and do not necessarily reflect those of the EU or the Health and Digital Executive Agency. Neither the EU nor the granting authority are responsible for them., aimed at improving privacy-preserving processing of data in the health domain. The technologies developed in the project will be demonstrated in four health-related use cases and with the involvement of SME's selected through an open funding call.

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关键词

Health Data,Data Processing,European Union,Magnetic Resonance Imaging,Medical Devices,Federation,Genetic Data,Patient Safety,Biobank,Privacy Issues,Process Flow,Magnetic Resonance Imaging Data,Cancer Care,Encrypted Data,Learning Management System,Health Technology Assessment,Secret Sharing,Federated Learning,Multi-party Computation,Health Data Research,Synthetic Data Generation,AI Models,Medical Device Regulation,Ultrasound Imaging,Control Points,Pseudonymized,Flow Data,Personal Data

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