Project description
Pioneering AI to prevent heart disease and diabetes
Non-communicable diseases like heart disease and diabetes are rising, posing significant challenges to public health. The EU-funded SHIELD project aims to tackle this using AI to prevent these conditions. SHIELD collects multimodal data from different actors in healthcare to create risk scores and personalised prevention strategies. These interventions, tested in Spain, Italy and Switzerland are delivered via a mobile app and they include behaviour change goals, lifestyle recommendations and health literacy content to reduce risk and progression. By guiding care plans with individual risk metrics, SHIELD seeks to improve prevention and management of cardiovascular disease and diabetes.
Objective
The prevalence of Non-Communicable Diseases is forcing countries to consider different initiatives aimed at reducing the burden and impact of these diseases.
In this sense, SHIELD pioneers an innovative approach to preventing cardiovascular diseases (CVD) and diabetes at all stages of disease and considering the strong relationship among them. Utilizing advanced AI, SHIELD offers personalized interventions following a hierarchical model based on patients' risk profiles. These profiles are continuously assessed through risk stratification and disease progression tools, leading to low, moderate, and high-risk layers, each requiring distinct prevention strategies, from halting disease progression to preventing relapse and complications.
Initial risk assessment will include genetics, demographics, socio-economic status, environment, behavior, and medical conditions, using datasets like SHARE or ELSA, and retrospective hospital data (4,500+ patients). Later-stage disease analysis will also entail polypharmacy, treatment adherence, wearables, psychosocial factors, PROMs, and PREMs, allowing for individualized interventions and real-time alerts for professionals through the SHIELD dashboard. SHIELD also prioritizes the quality and security of these data, creating a standardized data homogenization model and federated learning approach to keep sensitive data locally. Transparency is provided through explainable ML tools.
Interventions are accessible via mobile apps, providing resources, recommendations, education, and local services. Optimization algorithms enhance user engagement, and a chatbot, trained on patient data, offers continuous support with professional oversight.
SHIELD will be validated in 3 pilots, involving more than 2,300 individuals along 2 years. The aim is to get knowledge on the cost-effectiveness and efficacy of the prevention strategy proposed by SHIELD and to get insights for effective primary prevention pathways with population-wide impact.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.1 - Health
MAIN PROGRAMME
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HORIZON.2.1.1 - Health throughout the Life Course
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HORIZON.2.1.6 - Health Care Systems
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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.
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.
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.
HORIZON-RIA - HORIZON Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-HLTH-2024-STAYHLTH-01-two-stage
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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.
28036 Madrid
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.