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Watching the risk factors: Artificial intelligence and the prevention of chronic conditions

Project description

Empowering citizens and patients to take control of their health

It is believed that early risk prediction through the use of artificial intelligence can empower citizens to adopt healthier habits and a better lifestyle. The EU-funded WARIFA project aims to define a personalised early risk prediction model that will be used to support individual preventive measures as well as early intervention. The proposed technology can help empower both citizens and patients. The digital tool will mainly focus on three scenarios: the fight against skin cancer, the late complications of diabetes mellitus and the main lifestyle risk factors involved in noncommunicable diseases.

Objective

Digital healthcare may prevent poor health. Personalised early risk prediction by artificial intelligence can empower citizens to adopt healthier habits and a better lifestyle. This project aims at defining a general personalised early risk prediction model that will be used to support individual preventive measures as well as early intervention. New digital tools are designed to empower both citizens and patients. Furthermore, the impact of the new digital tools on health and care pathways are investigated. Three main scenarios are included: 1. Chronic sun damage and the fight against skin cancer, 2. The late complications of diabetes mellitus and 3. The four main lifestyle risk factors in noncommunicable diseases. In scenario 1, a smartphone application estimates a person`s risk for sun damage and skin cancer. Both healthy persons and skin cancer patients are included. The analysis is based on user-collected data indicating previous and current sun exposure, skin type including a computer-based naevus classification and the family history of skin cancer. Persons at increased risk are educated on healthy sun exposure behaviour including sun screen use. In addition, they are asked to see their doctor for a total body skin examination. In scenario 2, a smartphone application estimates a person`s risk for late complications of diabetes. General lifestyle measures as well as blood sugar levels collected by the patient are used as input for the analysis. Persons at increased risk for complications are given specific advice and are asked to see their doctor. In scenario 3, a web-based tool to collect general lifestyle data in healthy populations is tested, emphasising the four main risk factors: Unhealthy diet, physical inactivity, tobacco use and harmful use of alcohol. All data in the project are analysed in a multidisciplinary approach including medical, sociological and behavioural outcomes.

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

RIA - Research and Innovation action

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-SC1-DTH-2018-2020

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Coordinator

UNIVERSITETSSYKEHUSET NORD-NORGE HF
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 769 385,11
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 392 565,00

Participants (15)

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