Our PhD student, Nosa Aikodon from Liverpool John Moores University (LJMU), part of the TARGET research group, is set to deliver a compelling talk at the upcoming Research Roasters series in Liverpool. This public engagement event provides a unique opportunity for young researchers to discuss their scientific work with the general public.  

Every year, millions of people suffer from strokes linked to heart rhythm problems like atrial fibrillation. But what if we could predict who is most at risk—and why—using their own health data? This crucial question will be at the heart of the presentation by LJMU's Nosa Aikodon.  

In a short talk titled "Digital Twins for Personalised Stroke Prevention," Nosa will introduce the innovative concept of "digital twins": virtual versions of individual patients constructed from real-world hospital data. These advanced digital models serve as powerful tools to understand stroke risk, tailor treatments, and potentially prevent strokes before they occur. The discussion will also delve into how Artificial Intelligence (AI) can uncover hidden patterns and causes within complex medical data, revolutionizing personalized healthcare.  

Why attend?  

• Stroke risk affects millions globally, making this research highly relevant.  

• Discover how digital twins offer profound insights using individual health data.  

• Learn how AI can reveal hidden causes in complex medical cases, leading to more effective interventions.  

This event is happening on Wednesday, June 25, 2025, from 6:00 PM to 8:00 PM, at Lovelocks Coffee Shop in Liverpool. It's a fantastic chance for the public to connect directly with cutting-edge research that has the potential to significantly impact global health. Presented in collaboration with the TARGET Project, this talk highlights LJMU's dedication to pioneering research and promoting public understanding of science.  

Don't miss this opportunity!  

Secure your spot via the link. 

For more information, please visit: https://www.instagram.com/p/DKrUx9loGHu/?hl=en&img_index=1