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PRECISE4Q SIGNED

Personalised Medicine by Predictive Modeling in Stroke for better Quality of Life

Total Cost €

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EC-Contrib. €

0

Partnership

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 PRECISE4Q project word cloud

Explore the words cloud of the PRECISE4Q project. It provides you a very rough idea of what is the project "PRECISE4Q" about.

capability    lifestyle    data    registries    stroke    labelling    sources    gender    contrast    personalised    cohort    outcomes    socio    public    boosting    severe    therapy    cdss    sustainable    individual    simulation    planning    prediction    health    optimise    acute    models    electronic    semantic    tool    prevention    journey    platform    economic    rehab    predictive    reaching    decision    computer    treatment    heterogeneous    records    standardisation    worklife    clinical    ageing    medical    biochemical    stage    multidisciplinary    brain    model    hybrid    big    digital    form    create    gathering    perfusion    minimise    extraction    microbiomics    genomics    validated    strategies    prospective    substantial    risk    precise4q    learning    guidelines    architectures    qvidlab    society    biophysiological    mechanistic    clinicians    insurance    reintegration    deep    clinically    function    gradient    stages    life    requiring    retrospective    imaging    patients    social    schematic    coping    rehabilitation    time    burden    structured    precision    momentum    patient    efforts    dimensional    resilience    measurable    first   

Project "PRECISE4Q" data sheet

The following table provides information about the project.

Coordinator
CHARITE - UNIVERSITAETSMEDIZIN BERLIN 

Organization address
address: Chariteplatz 1
city: BERLIN
postcode: 10117
website: www.charite.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 5˙978˙245 €
 EC max contribution 5˙978˙245 € (100%)
 Programme 1. H2020-EU.3.1.5. (Methods and data)
 Code Call H2020-SC1-2017-CNECT-2
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-05-01   to  2022-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    CHARITE - UNIVERSITAETSMEDIZIN BERLIN DE (BERLIN) coordinator 1˙276˙250.00
2    TECHNOLOGICAL UNIVERSITY DUBLIN IE (DUBLIN) participant 1˙005˙000.00
3    EMPIRICA GESELLSCHAFT FUR KOMMUNIKATIONS UND TECHNOLOGIEFORSCHUNG MBH DE (BONN) participant 567˙750.00
4    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) participant 467˙205.00
5    LINKOPINGS UNIVERSITET SE (LINKOPING) participant 454˙225.00
6    MEDIZINISCHE UNIVERSITAT GRAZ AT (GRAZ) participant 398˙125.00
7    QMENTA IMAGING, SL ES (BARCELONA) participant 392˙500.00
8    FUNDACIO INSTITUT GUTTMANN ES (BADALONA) participant 377˙190.00
9    TARTU ULIKOOL EE (TARTU) participant 366˙250.00
10    DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH DE (KAISERSLAUTERN) participant 281˙250.00
11    UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN IE (DUBLIN) participant 273˙750.00
12    AOK NORDOST - DIE GESUNDHEITSKASSE DE (POSTDAM) participant 118˙750.00
13    INSTITIUID TEICNEOLAIOCHTA BHAILE ATHA CLIATH IE (DUBLIN) participant 0.00

Map

 Project objective

Stroke is one of the most severe medical problems with far-reaching public health and socio-economic impact, gathering momentum in an ageing society. PRECISE4Q sets out to minimise the burden of stroke for the individual and for society. It will create multi-dimensional data-driven predictive simulation computer models enabling – for the first time – personalised stroke treatment, addressing patient’s needs in four stages: prevention, acute treatment, rehabilitation and reintegration. Heterogeneous data from multidisciplinary sources will be integrated: genomics, microbiomics, biochemical; imaging including mechanistic biophysiological models of brain perfusion/function; social, lifestyle, gender; economic and worklife, requiring substantial efforts for information extraction, semantic labelling and standardisation. Novel hybrid model architectures, structured prediction models, complex deep-learning and gradient boosting models will form the Digital Stroke Patient Platform including a Stroke Risk CDSS (Clinical Decision Support System), Treatment Outcomes CDSS, Rehab Programme, Socio-Economic Planning Tool and New QvidLab. The decision support will be tailored to the patient's current life stage thus enabling clinicians to optimise prevention and treatment strategies over time, and will include personalised coping strategies, support of well-being and reintegration into social life and work. The predictive capability and clinical precision will be validated with real clinical data generated by (i) prospective clinical studies and (ii) retrospective analyses of big data sets: health registries, cohort studies, health insurance data, electronic health records. PRECISE4Q will have a clinically measurable and sustainable impact leading to better understanding of risk, health and resilience factors. In contrast to current schematic therapy guidelines, it will support patients throughout their life-long journey by personalised strategies for their specific needs.

 Deliverables

List of deliverables.
Use cases and their inputs/outputs specifications Documents, reports 2020-04-11 08:13:20
SoA for stroke risk factors, prognosis and outcomes Documents, reports 2020-04-11 08:13:19
Implementation of accessing and bridging functionalities Documents, reports 2020-04-11 08:13:19
Overview of data sources and a plan to access available data sources Documents, reports 2020-04-11 08:13:20
Written concept which is approved by the regulation authorities Documents, reports 2020-04-11 08:13:20
QoL targets for the models created in T4.5, T4.6, T4.7, T4.8 Documents, reports 2020-04-11 08:13:20
Electronic patient recorded outcome framework (ePRO) Documents, reports 2020-04-11 08:13:20
Study design rehabilitation/reintegration Documents, reports 2020-04-11 08:13:20
Categorized and ranked clinical challenges and needs Documents, reports 2020-04-11 08:13:19
White paper on hybrid model fusion strategies Documents, reports 2020-04-11 08:13:20
Project management plan and quality assurance process guidelines Documents, reports 2020-04-11 08:13:20
Corporate identity, branding policy, and project website Documents, reports 2020-04-11 08:13:20
Decision of build of the data warehouse Documents, reports 2020-04-11 08:13:20
Functional harmonization of Users, Roles and Access Documents, reports 2020-04-11 08:13:20
Study design for stroke treatment Documents, reports 2020-04-11 08:13:20
Communication and publication strategy Documents, reports 2020-04-11 08:13:20
Data Schema Designs for Each Model Documents, reports 2020-04-09 20:02:44
White paper on stroke risk, health and resilience factors Documents, reports 2020-04-09 20:02:36

Take a look to the deliverables list in detail:  detailed list of PRECISE4Q deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Effy Vayena, Alessandro Blasimme, I. Glenn Cohen
Machine learning in medicine: Addressing ethical challenges
published pages: e1002689, ISSN: 1549-1676, DOI: 10.1371/journal.pmed.1002689
PLOS Medicine 15/11 2020-04-11
2020 Blasimme, Alessandro and Vayena, Effy
The Ethics of AI in Biomedical Research, Patient Care and Public Health
published pages: , ISSN: , DOI:
Oxford Handbook of Ethics of Artificial Intelligence 2020-04-11
2019 Alejandro García-Rudolph, David Sánchez-Pinsach, Eloy Opisso Salleras, Josep María Tormos
Subacute stroke physical rehabilitation evidence in activities of daily living outcomes
published pages: e14501, ISSN: 0025-7974, DOI: 10.1097/md.0000000000014501
Medicine 98/8 2020-04-11
2019 Alessandro Blasimme, Effy Vayena, Ine Van Hoyweghen
Big Data, precision medicine and private insurance: A delicate balancing act
published pages: 205395171983011, ISSN: 2053-9517, DOI: 10.1177/2053951719830111
Big Data & Society 6/1 2020-04-11
2019 Alejandro Garcia-Rudolph, Sara Laxe, Joan Saurí, Montserrat Bernabeu Guitart
Stroke Survivors on Twitter: Sentiment and Topic Analysis From a Gender Perspective
published pages: e14077, ISSN: 1438-8871, DOI: 10.2196/14077
Journal of Medical Internet Research 21/8 2020-04-11

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