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CLARIFY SIGNED

Cancer Long Survivors Artificial Intelligence Follow Up

Total Cost €

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EC-Contrib. €

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Partnership

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Project "CLARIFY" data sheet

The following table provides information about the project.

Coordinator
SERVICIO MADRILENO DE SALUD 

Organization address
address: PLAZA CARLOS TRIAS BERTRAN 7
city: MADRID
postcode: 28020
website: http://cort.as/10Yf

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 Spain [ES]
 Total cost 4˙841˙962 €
 EC max contribution 4˙841˙962 € (100%)
 Programme 1. H2020-EU.3.1.5.1. (Improving halth information and better use of health data)
2. H2020-EU.3.1.3.2. (Transferring knowledge to clinical practice and scalable innovation actions)
 Code Call H2020-SC1-DTH-2019
 Funding Scheme RIA
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2022-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    SERVICIO MADRILENO DE SALUD ES (MADRID) coordinator 1˙018˙750.00
2    UNIVERSIDAD POLITECNICA DE MADRID ES (MADRID) participant 487˙500.00
3    NATIONAL UNIVERSITY OF IRELAND GALWAY IE (Galway) participant 486˙250.00
4    TECHNISCHE INFORMATIONSBIBLIOTHEK (TIB) DE (HANNOVER) participant 457˙000.00
5    UNIVERSITY COLLEGE LONDON UK (LONDON) participant 347˙500.00
6    HOLOS SOLUÇÕES AVANÇADAS EM TECNOLOGIAS DE INFORMAÇÃO, S.A. PT (CAPARICA, ALMADA) participant 346˙250.00
7    ACCENTURE GLOBAL SOLUTIONS LIMITED IE (DUBLIN) participant 335˙000.00
8    STELAR SECURITY TECHNOLOGY LAW RESEARCH UG DE (HAMBURG) participant 323˙750.00
9    GRUPO ESPANOL DE INVESTIGACION EN CANCER DE PULMON ES (BARCELONA) participant 295˙000.00
10    GRUPO ONCOLOGICO PARA EL TRATAMIENTO DE LAS ENFERMEDADES LINFOIDES - GOTEL ES (MADRID) participant 287˙500.00
11    UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN IE (DUBLIN) participant 241˙962.00
12    KRONOHEALTH SL ES (MURCIA) participant 215˙500.00

Map

 Project objective

There were 17 million new cases of cancer diagnosed worldwide in 2018. Survival rates of cancer patients were rather poor until recent decades, when diagnostic techniques have been improved and novel therapeutic options have been developed. It is estimated that more than 50% of adult patients diagnosed with cancer live at least 5 years in the US and Europe. This situation leads to a new challenge: to increase the cancer patients’ post-treatment quality of life and well-being. This proposal aims at identifying cancer survivors from three prevalent types of cancer, including breast, lung and lymphomas. The patient data will be collected from different Spanish hospitals and the selection will be based on ongoing health and supportive care needs of the particular patient types. We will determine the personalised factors that predict poor health status after specific oncological treatments. For this aim, Big Data and Artificial Intelligence techniques will be used to integrate all available patient´s information with publicly available relevant biomedical databases as well as information from wearable devices used after the treatment. To predict patient-specific risk of developing secondary effects and toxicities of their cancer treatments, we will build novel models based on statistical relational learning and explainable AI techniques on top of the integrated knowledge graphs. The models will utilise background knowledge of the associated cancer biology and thus will help clinicians to make evidence-based post-treatment decisions in a way that is not possible at all with any existing approach. In summary, CLARIFY proposes to integrate and analyse large volumes of heterogenous multivariate data to facilitate early discovery of risk factors that may deteriorate a patient condition after the end of oncological treatment. This will effectively help to stratify cancer survivors by risk in order to personalize their follow-up by better assessment of their needs.

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

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