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MAMMO1 SIGNED

Deep learning for mammography: Improving accuracy and productivity in breast cancer diagnosis.

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

MAMMO1 project word cloud

Explore the words cloud of the MAMMO1 project. It provides you a very rough idea of what is the project "MAMMO1" about.

waiting survival solutions demand tools changer doubts accurate mortality negatively game intervention radiologists techniques quality time delays mammo1 machine lists usefulness worldwide false women mammography cad marketed diagnosis cancer leads area images diminishing ground services workforce trained positives recall breaking decisions learning death single rates specificity supply prevent ultimately breast causes unnecessarily outperform scanning

Project "MAMMO1" data sheet

The following table provides information about the project.

Coordinator	KHEIRON MEDICAL TECHNOLOGIES LTD Organization address address: ROCKETSPACE, 40 ISLINGTON HIGH STREET city: LONDON postcode: N1 8EQ 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	United Kingdom [UK]
Project website	https://www.kheironmed.com/meet-mia
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 2019-01-01 to 2019-04-30

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	KHEIRON MEDICAL TECHNOLOGIES LTD KHEIRON MEDICAL TECHNOLOGIES LTD Organization address address: ROCKETSPACE, 40 ISLINGTON HIGH STREET city: LONDON postcode: N1 8EQ 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.	UK (LONDON)	coordinator	50˙000.00

Map

Project objective

Breast cancer is one of the main causes of death among women worldwide. Early diagnosis by mammography scanning is the best way to prevent mortality, but it requires the intervention of a highly trained workforce (radiologists). While the demand for radiologists is on the rise, the supply is quickly diminishing worldwide. This leads to long waiting lists and delays in getting a diagnosis, negatively affecting quality of services and ultimately survival rates. There is a strong need for tools that help radiologists make accurate decisions on mammography images in less time. CAD-based systems were developed to address this need; however, they have very low specificity, which leads to a high number of false positives, unnecessarily increasing the recall rates, and raising doubts about their usefulness. Mammo1 will be a game-changer in the area of breast cancer diagnosis by applying ground-breaking machine learning techniques, which are able to outperform all the currently marketed CAD-based solutions and even single radiologists.

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The information about "MAMMO1" are provided by the European Opendata Portal: CORDIS opendata.