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Trustworthy Artificial Intelligence for Personalised Risk Assessment in Chronic Heart Failure

Project description

Transforming heart failure care through trustworthy AI

Cardiovascular diseases continue to claim countless lives worldwide, with heart failure (HF) at the forefront of this health crisis. HF’s intricate web of causes, symptoms and unpredictable courses presents an urgent need for tailored care. In this context, the EU-funded AI4HF project will reshape the landscape of HF management. By harnessing the power of advanced AI, this project aims to develop a reliable and personalised approach to assessing and addressing HF risks. Its robust testing across diverse clinical centres and adherence to ethical AI development guidelines make it a beacon of hope for HF patients worldwide. AI4HF envisions a future where HF is met with precisely tailored, cutting-edge solutions.

Objective

Cardiovascular diseases remain the main cause of mortality worldwide; in particular, heart failure (HF) poses complex challenges in clinical practice, as it is associated with a significant variability in aetiologies, manifestations and risks, as well as in its progression and trajectories over time. Clinical risks of HF can vary from reduced cardiac function and regular hospitalisations, all the way to cardiac events and mortality. There is a need for a personalised medicine approach to tailor the care models (i.e. lifestyle changes, medications, interventions) to each HF patient’s risk profile and hence optimise the clinical outcomes. Artificial intelligence (AI) solutions trained from multi-source cardiovascular data have the potential to dissect the precise characteristics of each patient and predict their likely trajectories at an early stage. However, existing AI methods remain a far distance from clinical transfer and adoption due to a common and key limitation: their trustworthiness and acceptance by cardiologists and patients alike have not been achieved.

AI4HF will develop the first trustworthy AI solutions for personalised risk assessment and management of HF patients. The project will build on a unique set of big data repositories, trustworthy AI methods, computational tools and clinical results from major EU-funded projects in cardiology. To test robustness, fairness, transparency, usability and transferability, the validation with take place in eight clinical centres in both high- and low-to-middle-income countries in the EU and internationally. AI4HF will develop a comprehensive and standardised methodological framework for trustworthy and ethical AI development and evaluation based on the FUTURE-AI guidelines developed by the consortium members. AI4HF will be implemented through continuous multi-stakeholder engagement, taking into account clinical needs and patient preferences, as well as socio-ethical and regulatory perspectives.

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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 NETHERLANDS HEART INSTITUTE
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.

€ 429 125,00
Address
MOREELSEPARK 1
3511 EP UTRECHT
Netherlands

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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.

€ 429 125,00

Participants (14)

Partners (1)

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