Opendata, web and dolomites

FeatureCloud SIGNED

Privacy preserving federated machine learning and blockchaining for reduced cyber risks in a world of distributed healthcare

Total Cost €

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EC-Contrib. €

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Partnership

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 FeatureCloud project word cloud

Explore the words cloud of the FeatureCloud project. It provides you a very rough idea of what is the project "FeatureCloud" about.

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Project "FeatureCloud" data sheet

The following table provides information about the project.

Coordinator
TECHNISCHE UNIVERSITAET MUENCHEN 

Organization address
address: Arcisstrasse 21
city: MUENCHEN
postcode: 80333
website: www.tu-muenchen.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 4˙646˙000 €
 EC max contribution 4˙646˙000 € (100%)
 Programme 1. H2020-EU.3.1.5.1. (Improving halth information and better use of health data)
 Code Call H2020-SC1-FA-DTS-2018-1
 Funding Scheme RIA
 Starting year 2019
 Duration (year-month-day) from 2019-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TECHNISCHE UNIVERSITAET MUENCHEN DE (MUENCHEN) coordinator 1˙350˙000.00
2    SYDDANSK UNIVERSITET DK (ODENSE M) participant 523˙000.00
3    MEDIZINISCHE UNIVERSITAT GRAZ AT (GRAZ) participant 510˙000.00
4    PHILIPPS UNIVERSITAET MARBURG DE (MARBURG) participant 500˙000.00
5    SBA RESEARCH GEMEINNUTZIGE GMBH AT (WIEN) participant 500˙000.00
6    GNOME DESIGN SRL RO (SFANTU GHEORGHE) participant 453˙000.00
7    Concentris Research Management GmbH DE (Fürstenfeldbruck) participant 355˙000.00
8    UNIVERSITEIT MAASTRICHT NL (MAASTRICHT) participant 280˙000.00
9    RESEARCH INSTITUTE AG & CO KG AT (VIENNA) participant 175˙000.00

Map

 Project objective

The digital revolution, in particular big data and artificial intelligence (AI), offer new opportunities to transform healthcare. However, it also harbors risks to the safety of sensitive clinical data stored in critical healthcare ICT infrastructure. In particular data exchange over the internet is perceived insurmountable posing a roadblock hampering big data based medical innovations. FeatureCloud’s transformative security-by-design concept will minimize the cyber-crime potential and enable first secure cross-border collaborative data mining endeavors. FeatureCloud will be implemented into a software toolkit for substantially reducing cyber risks to healthcare infrastructure by employing the world-wide first privacy-by-architecture approach, which has two key characteristics: (1) no sensitive data is communicated through any communication channels, and (2) data is not stored in one central point of attack. Federated machine learning (for privacy-preserving data mining) integrated with blockchain technology (for immutability and management of patient rights) will safely apply next-generation AI technology for medical purposes. Importantly, patients will be given effective means of revoking previously given consent at any time. Our ground-breaking new cloud-AI infrastructure only exchanges learned model representations which are anonymous by default. Collectively, our highly interdisciplinary consortium from IT to medicine covers all aspects of the value chain: assessment of cyber risks, legal considerations and international policies, development of federated AI technology coupled to blockchaining, app store and user interface design, implementation as certifiable prognostic medical devices, evaluation and translation into clinical practice, commercial exploitation, as well as dissemination and patient trust maximization. FeatureCloud’s goals are bold, necessary, achievable, and paving the way for a socially agreeable big data era of the Medicine 4.0 age.

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The information about "FEATURECLOUD" are provided by the European Opendata Portal: CORDIS opendata.

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