Health virtual twins for the personalised management of stroke related to atrial fibrillation
TARGET aims to revolutionise the management of Atrial Fibrillation (AF) and AF-related strokes (AFRS). Despite extensive research and advancements in stroke prevention for AF patients, understanding the complex link between AF and stroke, as well as managing long-term risks, remains a challenge, posing substantial long-term risks such as stroke recurrence and bleeding complications. By developing novel virtual twin-based AI models, TARGET combines mechanistic and data-driven virtual twins with causal AI to bridge the gap between research and clinical practice. These models consider established risk factors, comorbidities, imaging, and biomarkers to create personalized approaches that optimize stroke management, rehabilitation treatments, and enhance patients' quality of life. The integration of these models into monitoring devices and rehabilitation tools accelerates clinical adoption, reducing healthcare costs and overcoming challenges faced by healthcare systems.
More information: https://researchportal.vub.be/en/publications/target-a-major-european-project-aiming-to-advance-the-personalise
Website: https://target-horizon.eu/
Funding: HORIZON-HLTH-2023-TOOL-05-03, HORIZON-RIA
RERE PI: Prof. Eva Swinnen & Prof. Marc Degelaen