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BigMedilytics SIGNED

Big Data for Medical Analytics

Total Cost €

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EC-Contrib. €

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Partnership

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Project "BigMedilytics" data sheet

The following table provides information about the project.

Coordinator
PHILIPS ELECTRONICS NEDERLAND BV 

Organization address
address: HIGH TECH CAMPUS 52
city: EINDHOVEN
postcode: 5656 AG
website: www.philips.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 Netherlands [NL]
 Project website http://www.bigmedilytics.eu
 Total cost 16˙940˙837 €
 EC max contribution 14˙997˙306 € (89%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2017-1
 Funding Scheme IA
 Starting year 2018
 Duration (year-month-day) from 2018-01-01   to  2021-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    PHILIPS ELECTRONICS NEDERLAND BV NL (EINDHOVEN) coordinator 1˙810˙068.00
2    FUNDACION PARA LA INVESTIGACION DEL HOSPITAL CLINICO DE LA COMUNITAT VALENCIANA, FUNDACION INCLIVA ES (VALENCIA) participant 1˙062˙136.00
3    ERASMUS UNIVERSITEIT ROTTERDAM NL (ROTTERDAM) participant 1˙010˙002.00
4    DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH DE (KAISERSLAUTERN) participant 850˙625.00
5    REGION STOCKHOLM SE (STOCKHOLM) participant 836˙000.00
6    CHARITE - UNIVERSITAETSMEDIZIN BERLIN DE (BERLIN) participant 784˙956.00
7    ERASMUS UNIVERSITAIR MEDISCH CENTRUM ROTTERDAM NL (ROTTERDAM) participant 710˙000.00
8    IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD IL (PETACH TIKVA) participant 703˙937.00
9    UNIVERSITY OF SOUTHAMPTON UK (SOUTHAMPTON) participant 599˙450.00
10    STICHTING OLVG NL (AMSTERDAM) participant 596˙475.00
11    STICHTING ELISABETH-TWEESTEDEN ZIEKENHUIS NL (TILBURG) participant 541˙250.00
12    INSTITUTO TECNOLOGICO DE INFORMATICA ES (VALENCIA) participant 483˙250.00
13    HUAWEI TECHNOLOGIES DUESSELDORF GMBH DE (DUSSELDORF) participant 366˙187.00
14    SERVICIO MADRILENO DE SALUD ES (MADRID) participant 359˙375.00
15    INSTITUT CURIE FR (PARIS) participant 341˙250.00
16    TECHNISCHE UNIVERSITEIT EINDHOVEN NL (EINDHOVEN) participant 332˙936.00
17    CONTEXTFLOW GMBH AT (WIEN) participant 324˙975.00
18    ATOS SPAIN SA ES (MADRID) participant 300˙125.00
19    ROYAL COLLEGE OF SURGEONS IN IRELAND IE (DUBLIN) participant 295˙866.00
20    "NATIONAL CENTER FOR SCIENTIFIC RESEARCH ""DEMOKRITOS""" EL (AGIA PARASKEVI) participant 284˙000.00
21    OPTIMEDIS AG DE (HAMBURG) participant 281˙225.00
22    PRIVREDNO DRUSTVO ZA PRUZANJE USLUGA ISTRAZIVANJE I RAZVOJ NISSATECH INNOVATION CENTRE DOO RS (NIS) participant 244˙125.00
23    GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER DE (HANNOVER) participant 230˙000.00
24    UNIVERSIDAD POLITECNICA DE MADRID ES (MADRID) participant 230˙000.00
25    NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK ONDERZOEK TNO NL (DEN HAAG) participant 199˙977.00
26    UNIVERSITAETSKLINIKUM ESSEN DE (ESSEN) participant 184˙000.00
27    ATHENS TECHNOLOGY CENTER ANONYMI BIOMICHANIKI EMPORIKI KAI TECHNIKI ETAIREIA EFARMOGON YPSILIS TECHNOLOGIAS EL (ATHINA) participant 163˙625.00
28    MY MHEALTH LIMITED UK (BOURNEMOUTH DORSET) participant 144˙375.00
29    MEDIZINISCHE UNIVERSITAET WIEN AT (WIEN) participant 134˙475.00
30    HASSO-PLATTNER-INSTITUT FOR DIGITAL ENGINEERING GGMBH DE (POTSDAM) participant 111˙750.00
31    ACHMEA BV NL (ZEIST) participant 100˙012.00
32    Teknologian tutkimuskeskus VTT Oy FI (Espoo) participant 100˙000.00
33    AOK NORDOST - DIE GESUNDHEITSKASSE DE (POSTDAM) participant 97˙125.00
34    ASTRAZENECA UK LIMITED UK (CAMBRIDGE) participant 96˙250.00
35    GIE AXA FR (PARIS) participant 87˙500.00

Map

 Project objective

There are three main reasons for an immediate innovation action to apply big data technologies in Healthcare. Firstly, a Healthy nation is a Wealthy nation! An improvement in health leads to economic growth through long-term gains in human and physical capital, which ultimately raises productivity and per capita GDP. Secondly, Healthcare is one of the most expensive sectors, which accounts for 10% of the EU’s GDP continuously becoming more expensive. Thirdly, as healthcare is traditionally very conservative with adopting ICT, while big healthcare data is becoming available, the expected impact of applying big data technologies in Healthcare is enormous. BigMedilytics will transform Europe’s Healthcare sector by using state-of-the-art Big Data technologies to achieve breakthrough productivity in the sector by reducing cost, improving patient outcomes and delivering better access to healthcare facilities simultaneously, covering the entire Healthcare Continuum – from Prevention to Diagnosis, Treatment and Home Care throughout Europe. BigMedilytics produces: • A Big Data Healthcare Analytics Blueprint (defining platforms and components), which enables data integration and innovation spanning all the key players across the Healthcare Data Value Chains • Instantiations of the Blueprint which implement BigMedilytics concepts across 12 large-scale pilots accounting for an estimated 86% of deaths and 77% of the disease burden in Europe • The Best “Big Data technology and Healthcare policy” Practices related to big data technologies, new business models and European and national healthcare data policies and regulations. BigMedilytics will maximize the impact by using its Big Data Healthcare Analytics Blueprint and the Best Practices to scale-up the concepts demonstrated in the 12 pilots, to the whole Healthcare sector in Europe. It will use health records of more than 11 million patients across 8 countries and data from other sectors such as insurance and public sector.

 Deliverables

List of deliverables.
T0 base line measurement of the KPIs Documents, reports 2020-04-11 04:55:55
Country specific infographics that summarize the relevant regulations for Big data technologies in the healthcare sector Documents, reports 2020-04-11 04:55:55
Dissemination procedures Documents, reports 2020-04-11 04:55:55
Website portal Documents, reports 2020-04-11 04:55:55
Intermediate report on dissemination activities Documents, reports 2020-04-11 04:55:56
Communication plan and tools Documents, reports 2020-04-11 04:55:55
Initial prototypes of specific components for all BigMedilytics pilots (software) Documents, reports 2020-04-11 04:55:55
Updated prototypes of specific components for all BigMedilytics pilots (software) Documents, reports 2020-04-11 04:55:55

Take a look to the deliverables list in detail:  detailed list of BigMedilytics deliverables.

 Publications

year authors and title journal last update
List of publications.
2020 Jose Luis Holgado, Cristina Lopez, Antonio Fernandez, Inmaculada Sauri, Ruth Uso, Jose Luis Trillo, Sara Vela, Julio Nuñez, Josep Redon, Adrian Ruiz
Acute kidney injury in heart failure: a population study
published pages: , ISSN: 2055-5822, DOI: 10.1002/ehf2.12595
ESC Heart Failure 2020-04-11
2019 Nils Rethmeier, Barbara Plank
MoRTy: Unsupervised Learning of Task-specialized Word Embeddings by Autoencoding
published pages: 49-54, ISSN: , DOI: 10.18653/v1/w19-4307
Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019) 2020-04-11
2018 Veeningen, Meilof; Chatterjea, Supriyo; Horváth, Anna Zsófia; Spindler, Gerald; Boersma, Eric; Spek, Peter; Galiën, Onno; Gutteling, Job; Kraaij, Wessel; Veugen, Thijs
Enabling analytics on sensitive medical data with secure multi-party computation
published pages: , ISSN: , DOI: 10.3233/978-1-61499-852-5-76
2 2020-04-11
2018 Thaler, Stefan; Menkovski, Vlado; Petkovic, Milan
Deep Learning in Information Security
published pages: , ISSN: , DOI:
1 2020-04-11
2019 Gaurav Vashisth, Jan-Niklas Voigt-Antons, Michael Mikhailov, Roland Roller
Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations
published pages: 348-358, ISSN: , DOI: 10.18653/v1/w19-5037
Proceedings of the 18th BioNLP Workshop and Shared Task 2020-04-11

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

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