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Disruptive Artificial Intelligence engine to facilitate rapid low cost development of specialist e-health applications for smart decision making in medical pre-diagnosis

Total Cost €


EC-Contrib. €






 Al-medicare project word cloud

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

companies    mainly    health    expand    diagnostic    b2b    decision    machine    vcs    professional    providers    time    adapt    life    shortage    environment    optimize    building    patients    provides    learning    ehr    3rd    conduct    foundation    engines    toolset    lack    validate    co    least    apps    market    performance    people    services    solution    developers    countries    unfortunately    saving    public    digital    experts    base    lives    misdiagnosed    rarity    model    attractive    limited    cooperation    techniques    commercialize    diagnosis    party    framework    money    workers    refine    healthcare    start    founders    ai    months    share    demonstration    takes    clinical    05    practices    infermedica    thousands    recommends    medicare    disruption    complete    engage    innovation    15    medical    platform    practitioners    strategy    significantly    first    10    1000    individual    license    ups    few    rely    al    global    business   

Project "Al-medicare" data sheet

The following table provides information about the project.


Organization address
address: PLAC SOLNY 14/3
postcode: 50-062
website: n.a.

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 Poland [PL]
 Project website
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3.1.4. (Active ageing and self-management of health)
2. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
3. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
4. H2020-EU.3.1.6. (Health care provision and integrated care)
 Code Call H2020-SMEINST-1-2016-2017
 Funding Scheme SME-1
 Starting year 2017
 Duration (year-month-day) from 2017-02-01   to  2017-05-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

10-15% of all medical cases in developed countries are misdiagnosed, mainly due to medical practitioners’ lack of experience, limited time for diagnosis and rarity of the conditions. Furthermore, there is an increasing global shortage of healthcare workers. WHO recommends at least 2.3 health workers per 1000 people, unfortunately yet some countries have 0.05 per 1000 people. To address this need, Infermedica has developed a medical diagnostic framework AI-medicare which for the first time provides a complete toolset for 3rd party developers of medical apps and services to build advanced clinical decision support systems. Our solution enables digital health developers to achieve at low cost and short time what currently takes months, saving thousands of lives and public money. To do so, co-founders rely on their cooperation with professional partners, medical experts, and VCs. Today there are just a few companies which try to develop diagnostic engines to improve clinical decision-making. However, they do it without meaningful disruption of current medical practices, and they do not share their AI engines. For that, Al-medicare open medical platform is particularly attractive for IT companies building healthcare products or services for patients and providers like research institutions, EHR platform providers, start-ups and individual developers. To fully commercialize this EU-based technology, a comprehensive business model was proposed. Future growth will be driven by B2B model based on the license. In Phase 1, we will conduct global market studies of the digital health market, develop an innovation management strategy and identify and engage development and demonstration partners. In Phase 2, we will significantly expand and refine the medical knowledge base which is the foundation of the framework, validate and test the diagnostic framework in a real-life environment and adapt advanced machine learning techniques to expand and optimize AI-medicare performance.

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The information about "AL-MEDICARE" are provided by the European Opendata Portal: CORDIS opendata.

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