Opendata, web and dolomites

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

Views

0

 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.

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

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

 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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "MRDOC" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.3.;H2020-EU.2.3.;H2020-EU.2.1.)

Colourganisms (2020)

Microbial production of custom-made, pure and sustainable anthocyanins

Read More  

TAPPXSSAI (2019)

Development of a system for automatic ad insertion into on-demand streaming video to provide new monetization mechanisms to the media industry

Read More  

RoboSynFarm (2019)

Robotic Synthesis Farm

Read More