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DEVELOPING TRUSTWORTHY ARTIFICIAL INTELLIGENCE (AI)-DRIVEN TOOLS TO PREDICT VASCULAR DISEASE RISK AND PROGRESSION

Project description

AI to help predict cardiovascular disease progression

Cardiovascular diseases (CVDs), including abdominal aortic aneurysm (AAA) and peripheral arterial disease (PAD), remain leading causes of morbidity and mortality globally. Identifying patients at high risk of disease progression and cardiovascular events is crucial for effective treatment. Existing methods lack the ability to provide personalised predictions. More accurate, data-driven approaches are needed. The EU-funded VASCUL-AID project will develop an AI-driven platform that predicts the risk of AAA and PAD progression. By integrating multi-source data such as imaging, proteomics, genomics, and lifestyle data, the platform delivers personalised, evidence-based care. It includes tools for risk prediction, decision-making, and patient engagement. VASCUL-AID aims to serve as a model for broader applications in other cardiovascular diseases.

Objective

The aim of VASCUL-AID is to predict the risk of cardiovascular events and progression of the vascular diseases Abdominal Aortic Aneurysm (AAA) and Peripheral Arterial Disease (PAD) to influence the course of disease improving the patient’s quality of life and care and assisting clinicians to make better-informed decisions involving the patient. VASCUL-AID will allow us for the first time to identify patients who are at high risk for AAA growth or PAD progression and cardiovascular events. To this end, we will deliver a clinically relevant and cost-effective trustworthy AI-driven platform (VASCUL-AID) that integrates multi-source parameters including imaging, proteomic and genomic data as well as life-style patient data from wearables to enable personalised vascular disease management. To maximise the personalised prevention strategies, VASCUL-AID leverages visualisation tools to improve clinician-patient communication and empower the patient. The VASCUL-AID platform consists of AI risk-prediction tools, a patient communication app an a clinical dashboard to support clinical decision-making. A particular emphasis is placed on ethics, to ensure beneficial implementation of AI prediction tools.
In this project, we aim to (1) build an EU-wide data infrastructure, (2) develop an AI-based progression prediction tools for AAA and PAD, (3) develop criteria according to the COMET initiative to assess the effectiveness of VASCUL-AID, and (4) clinically test and show proof-of-concept for the VASCUL-AID platform. Once validated, this platform can be extended to other cardiovascular diseases (CVDs) as well. VASCUL-AID brings together 14 leading organisations (and 2 affiliated entities) consisting of clinical academic centres, institutes, universities and SMEs as well as large industry, patients organisations and policy makers that cover the full value chain to enable integration of the platform into clinical practice.

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Keywords

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-HLTH-2022-STAYHLTH-01-two-stage

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Coordinator

STICHTING AMSTERDAM UMC
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.

€ 1 931 131,25
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.

€ 1 931 131,25

Participants (12)

Partners (2)

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