TARGET

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.

TARGET is co-funded by the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101136244.