Imagine a smart weather forecast, but for your arteries. Instead of just seeing a problem now, this tool uses a mix of medical scans, genetic codes, and smartwatch data to predict if a blood vessel will bulge or clog in the future. It then gives doctors a clear dashboard and patients an app to help them decide on the best treatment together.
Clinicians currently lack a precise way to identify which patients with abdominal aortic aneurysms or peripheral arterial disease are at the highest risk for rapid progression or cardiovascular events.
An AI-driven platform featuring risk-prediction tools, a patient communication app, and a clinical decision-support dashboard.
If you are a health-tech AI developer dealing with the lack of integrated vascular data — this project developed a trustworthy AI-driven platform that combines imaging, proteomics, and genomics to predict disease progression. This allows for the creation of high-precision clinical decision tools.
If you are a wearable health device manufacturer dealing with low clinical utility of lifestyle data — this project developed a system that integrates wearable data into a clinical dashboard. This transforms raw activity data into actionable risk-prediction for vascular events.
If you are a private cardiology clinic network dealing with inefficient patient triaging — this project developed AI risk-prediction tools for AAA and PAD. This enables the identification of high-risk patients for targeted, personalized prevention strategies.
Based on available project data, the specific commercial price is not mentioned, although the project aims to deliver a cost-effective platform.
Yes. The project documentation states that once validated, the platform can be extended to other cardiovascular diseases (CVDs) as well.
Based on available project data, specific licensing terms are not provided, but the project involves a consortium of 15 partners including industry and universities.
The project places a particular emphasis on ethics to ensure the beneficial implementation of AI prediction tools and builds an EU-wide data infrastructure.
The project period runs from 2023-05-01 to 2029-04-30, indicating a long-term development and validation cycle.
The consortium is heavily weighted toward research and academia, with 7 universities and 4 research institutes. However, it maintains a 13% industry ratio with 2 industry partners, ensuring that the 15-partner group covers the full value chain from data collection to clinical practice integration.
Contact Stichting Amsterdam UMC in the Netherlands
Contact us to explore licensing opportunities for the VASCUL-AID AI risk-prediction tools.
