Projekt
Trustworthy Artificial Intelligence for Personalised Risk Assessment in Chronic Heart Failure
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…
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.
Themengebiete
- Gesundheit Gesundheit – Überblick über Forschungsprojekte, Patente und Akteure im TechnologieAtlas.
Hochschulen
- STICHTING NETHERLANDS HEART INSTITUTE STICHTING NETHERLANDS HEART INSTITUTE – Hochschule bzw. Forschungseinrichtung mit Aktivitäten in Forschung un…
- MUHIMBILI UNIVERSITY OF HEALTH AND ALLIED SCIENCES MUHIMBILI UNIVERSITY OF HEALTH AND ALLIED SCIENCES – Hochschule bzw. Forschungseinrichtung mit Aktivitäten in…
- UNIVERSITAIR MEDISCH CENTRUM UTRECHT UNIVERSITAIR MEDISCH CENTRUM UTRECHT – Hochschule bzw. Forschungseinrichtung mit Aktivitäten in Forschung und…
- UNIVERSITAT DE BARCELONA UNIVERSITAT DE BARCELONA – Hochschule bzw. Forschungseinrichtung mit Aktivitäten in Forschung und Innovation.
- THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD – Hochschule bzw. Forschungseinrichtung mit…
- FUNDACIO HOSPITAL UNIVERSITARI VALL D'HEBRON - INSTITUT DE RECERCA FUNDACIO HOSPITAL UNIVERSITARI VALL D'HEBRON - INSTITUT DE RECERCA – Hochschule bzw. Forschungseinrichtung mi…
Unternehmen
- REGENOLD GMBH REGENOLD GMBH – Unternehmen mit Aktivitäten in Forschung und Innovation.