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MrDoc SIGNED

Development and commercialization of a semi-supervised learning AI for robust diagnosis in real world settings.

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 MrDoc project word cloud

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

learning    blood    semi    providers    led    waiting    rate    labelled    pharmaceutical    smartphone    dirty    errors    haemoglobin    inputs    apps    examination    diseases    accurate    human    companies    noisy    overcoming    detection    electronics    positively    creative    local    usually    platform    consume    tools    non    practitioners    health    selling    world    additional    detect    licence    egcs    cured    glucose    despite    financial    negative    incomplete    consumers    healthcare    burden    owners    limited    ing    discouraged    positive    cameras    tests    huge    dataset    solutions    solution    difficulties    symptoms    timeframe    signals    heart    technological    interpret    don    arrhythmia    limitations    closed    ai    check    gp    biometric    labelling    simply    false    people    pressure    death    economies    patients    accuracy    software    producers    mimics    amounts    medical    smartphones    cardiovascular    hardware    supervised    data    communicable    final    variability    circuit    time    advancements    diagnose    camera    diabetes    train    invasiveness    imagination    examinations    ncds    cardiac    hypertension    original   

Project "MrDoc" data sheet

The following table provides information about the project.

Coordinator
MR DOC SRL 

Organization address
address: VIA PIETRO BLASERNA 40
city: ROMA
postcode: 146
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 Italy [IT]
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2019
 Duration (year-month-day) from 2019-08-01   to  2020-01-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MR DOC SRL IT (ROMA) coordinator 50˙000.00

Map

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

Non-communicable diseases such as cardiovascular diseases, diabetes, are by far the leading cause of death in the world and a growing burden for patients, healthcare providers and local economies. Despite many NCDs conditions like cardiac arrhythmia, diabetes, hypertension can be cured with early detection, they don’t often show symptoms. During their medical check-up, medical practitioners (GP) can’t be accurate as specific examinations (e.g. EGCs, blood tests), resulting in a growing number of errors or false negative/positive, which represent for Healthcare systems and additional financial burden. People are usually discouraged from doing specific examination due to long waiting time, invasiveness of medical tests and additional costs.Even if technological advancements have led to AI based easy-to-use solutions able to contribute positively to easy and early detection of diseases and pre-diseases condition, they come along with many significant limitations, such as the need to train on huge amounts of labelled data and difficulties in managing inputs that are noisy, incomplete or simply different from the original dataset (such data generated from a smartphone camera).This results in limited accuracy or significant costs and time consume for labelling of data. We have developed a platform based on a semi-supervised learning AI, able to analyse and interpret medical dataset through a process that mimics human creative imagination and, in a very short timeframe, detect and diagnose some NCDs and biometric parameters (blood pressure, Heart rate variability, haemoglobin, blood glucose) from “dirty” signals, generated by consumer electronics devices (smartphones, closed circuit cameras, etc.), with a high level of accuracy overcoming existing limitations.We aim at selling and licence our solution to 3 main targets: - final consumers/patients, - producers/owners of software and hardware tools (as well as Apps) in Health sector, Pharmaceutical companies.

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

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