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.
Consortium members
- Amsterdam UMC
- Brightfish
- Oxford University
- University of Twente
- University of Porto
- University of Aveiro
- Centro hospitalar de Sao Joao
- Centre Hospitalier Universitaire de Nice
- ALLAI
- University of Belgrade
- HUS
- Vinca Institute of Nuclear Sciences
- University of Bergen
- Brandenburg medical school
- Asklepios Kliniken Hamburg
- Cardioangiologisches Centrum Bethanien
