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Finding Endometriosis using Machine Learning

Objective

The framework 'P4 Medicine' (predictive, preventative, personalized, participatory) was developed to detect and prevent disease through close monitoring, deep statistical analysis, biomarker testing, and patient health coaching to best use the limited healthcare resources and produce maximum benefit for all patients. However, we have seen only few feasible examples over the past 10 years.

The Finding Endometriosis using Machine Learning (FEMaLe) project will revitalise the concept to develop and demonstrate the Scalable Multi-Omics Platform (SMOP) that converts multi-omic person population datasets into a personalised predictive model to improve intervention along the continuum of care for people with endometriosis. We will design, validate and implement a comprehensive model for the detection and management of people with endometriosis to facilitate shared decision making between the patient and the healthcare provider, enable the delivery of precision medicine, and drive new discoveries in endometriosis treatment to deliver novel therapies and improve quality of life for patients.

We will rely on participatory processes, advanced computer sciences, state-of-the-art technologies, and patient-shared data to deliver: 1) mobile health app for people with endometriosis,
2) three clinical decision support (CDS) tools for targeted healthcare providers (risk stratification tool for general practitioners, multi-marker signature tool for gynaecologists, and non-invasive diagnostic tool for radiologist), and
3) computer vision-based software tool for real time augmented reality guided surgery of endometriosis.

Health maintenance organisations (HMO) expect to be able to reduce overall cost of treatment by at least 20%, while improving patient outcomes, using CDS tools. The SMOP will be based on open protocol, embedded in all ethical and legal frameworks, to enable tailored and personalised usage to improve the lives of patients across Europe beyond the project period.

Field of science

  • /natural sciences/computer and information sciences/artificial intelligence/machine learning

Call for proposal

H2020-SC1-DTH-2020-1
See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Coordinator

AARHUS UNIVERSITET
Address
Nordre Ringgade 1
8000 Aarhus C
Denmark
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 927 418,25

Participants (15)

AARHUS UNIVERSITETSHOSPITAL
Denmark
EU contribution
€ 248 155
Address
Palle Juul-jensens Boulevard 99
8200 Aarhus
Activity type
Research Organisations
EUROPEAN SOCIETY FOR QUALITY AND PATIENT SAFETY IN GENERAL PRACTICE/FAMILY MEDICINE
Denmark
EU contribution
€ 194 818,75
Address
Ega Engvej 60
8250 Ega
Activity type
Research Organisations
SEMMELWEIS EGYETEM
Hungary
EU contribution
€ 266 387,50
Address
Ulloi Utca 26
1085 Budapest
Activity type
Higher or Secondary Education Establishments
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
United Kingdom
EU contribution
€ 722 040
Address
Wellington Square University Offices
OX1 2JD Oxford
Activity type
Higher or Secondary Education Establishments
SURGAR
France
EU contribution
€ 712 350
Address
Biopole Clermont Limagne
63360 Saint-beauzire
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
RIGAS TEHNISKA UNIVERSITATE
Latvia
EU contribution
€ 375 470
Address
Kalku Iela 1
1658 Riga
Activity type
Higher or Secondary Education Establishments
KUNGLIGA TEKNISKA HOEGSKOLAN
Sweden
EU contribution
€ 176 863,75
Address
Brinellvagen 8
100 44 Stockholm
Activity type
Higher or Secondary Education Establishments
ISTANBUL AVRUPA ARASTIRMALARI DERNEGI
Turkey
EU contribution
€ 157 882,50
Address
Cumhuriyet Mah. D-100 Karayolu-cadde Aklama-istanbul Outlet Park Ickapino:282
34522 Istanbul
Activity type
Research Organisations
PRECISIONLIFE LTD
United Kingdom
EU contribution
€ 176 863,75
Address
Unit 8B Bankside, Hanborough Business Park, Long Hanborough
OX29 8LJ Witney
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
YOURCODE LAB INFORMATIKAI, SZOLGALTATO ES TANACSADO KORLATOLT FELELOSSEGU TARSASAG
Hungary
EU contribution
€ 139 267,50
Address
Bajcsy-zsilinszky Koz 2 6/5
1065 Budapest
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
THE UNIVERSITY COURT OF THE UNIVERSITY OF ABERDEEN
United Kingdom
EU contribution
€ 422 051,25
Address
King's College Regent Walk
AB24 3FX Aberdeen
Activity type
Higher or Secondary Education Establishments
CORRELATE AS
Norway
EU contribution
€ 226 080
Address
Cort Adelers Gate 17
0254 Oslo
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
NEMANJA TODIC PREDUZETNIK WEB BAY
Serbia
EU contribution
€ 85 280
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EGYUTT KONNYEBB NOI EGESZSEGERT ALAPITVANY
Hungary
EU contribution
€ 62 453,75
Address
Szekacs Utca 24. Fszt./1.
1122 Budapest
Activity type
Other
THE UNIVERSITY OF EDINBURGH
United Kingdom
EU contribution
€ 50 752,50
Address
Old College, South Bridge
EH8 9YL Edinburgh
Activity type
Higher or Secondary Education Establishments