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DeepHealth SIGNED

Deep-Learning and HPC to Boost Biomedical Applications for Health

Total Cost €

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EC-Contrib. €

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Partnership

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 DeepHealth project word cloud

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

environments    time    learning    ing    crs4    group    flexible    uniformity    trained    paradigm    techniques    expert    tools    relies    philips    data    computing    gathering    ways    piaf    deephealth    commitment    software    countries    thales    decision    commercial    heterogeneous    framework    migraine    scientific    staff    environment    underpin    model    performance    health    analytics    eddll    library    science    final    compatible    hospitals    compatibility    biomedical    deep    industrial    training    six    infrastructures    unifying    separated    diseases    scalable    sustainability    libraries    tracking    ones    validated    distributed    treatment    service    cea    measured    innovation    dl    power    clinical    21    ranging    oriented    expressif    train    multidisciplinary    ttmip    fourth    digital    supercomputing    14    vision    computer    centers    platforms    monitoring    medical    hpc    trade    big    move    discovery    dementia    models    solution    datasets    diagnosis    depression    ecvl    pathology    sme    standardise    efficient   

Project "DeepHealth" data sheet

The following table provides information about the project.

Coordinator
EVERIS SPAIN SL 

Organization address
address: AVENIDA MANOTERAS 52
city: MADRID
postcode: 28050
website: www.everis.com

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 Spain [ES]
 Total cost 14˙642˙324 €
 EC max contribution 12˙774˙824 € (87%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2018-2
 Funding Scheme IA
 Starting year 2019
 Duration (year-month-day) from 2019-01-01   to  2021-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    EVERIS SPAIN SL ES (MADRID) coordinator 741˙697.00
2    COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES FR (PARIS 15) participant 1˙570˙020.00
3    PHILIPS MEDICAL SYSTEMS NEDERLAND BV NL (BEST) participant 941˙576.00
4    UNIVERSITAT POLITECNICA DE VALENCIA ES (VALENCIA) participant 907˙129.00
5    CENTRO DI RICERCA, SVILUPPO E STUDI SUPERIORI IN SARDEGNA SOCIETÀ A RESPONSABILITÀ LIMITATA IT (PULA CAGLIARI) participant 832˙500.00
6    BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION ES (BARCELONA) participant 798˙062.00
7    UNIVERSITA DEGLI STUDI DI TORINO IT (TORINO) participant 713˙250.00
8    SIVECO ROMANIA SA RO (BUCURESTI) participant 671˙125.00
9    THALES SIX GTS FRANCE SAS FR (GENNEVILLIERS) participant 651˙311.00
10    OTTO-VON-GUERICKE-UNIVERSITAET MAGDEBURG DE (MAGDEBURG) participant 636˙875.00
11    PRO DESIGN Electronic GmbH DE (Bruckmuehl) participant 584˙850.00
12    UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMILIA IT (MODENA) participant 561˙031.00
13    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE CH (LAUSANNE) participant 522˙543.00
14    WINGS ICT SOLUTIONS INFORMATION & COMMUNICATION TECHNOLOGIES IKE EL (NEA SMYRNI) participant 444˙937.00
15    STELAR SECURITY TECHNOLOGY LAW RESEARCH UG DE (HAMBURG) participant 398˙250.00
16    AZIENDA OSPEDALIERA CITTA DELLA SALUTE E DELLA SCIENZA DI TORINO IT (TORINO) participant 381˙250.00
17    TREE TECHNOLOGY SA ES (SIERO) participant 322˙000.00
18    FUNDACION PARA EL FOMENTO DE LA INVESTIGACION SANITARIA Y BIOMEDICA DE LA COMUNITAT VALENCIANA ES (VALENCIA) participant 317˙375.00
19    SPITALUL CLINIC PROF DR THEODOR BURGHELE RO (BUCARESTI) participant 293˙750.00
20    CENTRE HOSPITALIER UNIVERSITAIRE VAUDOIS CH (LAUSANNE) participant 199˙038.00
21    REGION STOCKHOLM SE (STOCKHOLM) participant 150˙000.00
22    KAROLINSKA INSTITUTET SE (STOCKHOLM) participant 136˙250.00

Map

 Project objective

Health scientific discovery and innovation are expected to quickly move forward under the so called “fourth paradigm of science”, which relies on unifying the traditionally separated and heterogeneous high-performance computing and big data analytics environments. Under this paradigm, the DeepHealth project will provide HPC computing power at the service of biomedical applications; and apply Deep Learning (DL) techniques on large and complex biomedical datasets to support new and more efficient ways of diagnosis, monitoring and treatment of diseases. DeepHealth will develop a flexible and scalable framework for the HPC Big Data environment, based on two new libraries: the European Distributed Deep Learning Library (EDDLL) and the European Computer Vision Library (ECVL). The framework will be validated in 14 use cases which will allow to train models and provide training data from different medical areas (migraine, dementia, depression, etc.). The resulting trained models, and the libraries, will be integrated and validated in 7 existing biomedical software platforms, which include: a) commercial platforms (e.g. PHILIPS Clinical Decision Support System from or THALES SIX PIAF; and b) research oriented platforms (e.g. CEA`s ExpressIF™ or CRS4`s Digital Pathology). Impact is measured by tracking the time-to-model-in-production (ttmip). Through this approach, DeepHealth will also standardise HPC resources to the needs of DL applications, and underpin the compatibility and uniformity on the set of tools used by medical staff and expert users. The final DeepHealth solution will be compatible with HPC infrastructures ranging from the ones in supercomputing centers to the ones in hospitals. DeepHealth involves 21 partners from 9 European Countries, gathering a multidisciplinary group from research organisations (9), health organisations (4) as well as (4) large and (4) SME industrial partners, with strong commitment towards innovation, exploitation and sustainability.

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

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