Built by Science: From Mini-Organs to Machine Minds

Urinary tract infections (UTI) are widespread diseases that require lengthy treatments. Nevertheless, an increasing number of patients experience re-appearance of UTI despite treatment. Albeit the substantial impact of UTI to our healthcare system and the wellbeing of patients, studies about UTI mainly focus on mouse models that cannot mimic the human urinary tract. Here, we present a lab-developed human bladder tissue that replicates key features of the human urinary tract. We use this model to better understand how infectious bacteria interact with this human environment and how our tissues fight back.

How can AI help doctors make better decisions? That’s the question we’re exploring in our research. We use machine learning to build systems that learn from clinical data, laboratory measurements, and molecular profiles – trying to spot hidden patterns that could help detect diseases earlier and more accurately. These AI-powered decision support tools are part of a growing movement to make healthcare smarter and more personalized. By combining technology with medical expertise, we aim to make complex data understandable and useful – both for researchers and for the doctors of tomorrow.

Artificial intelligence (AI) is having a major impact on radiology, rapidly analyzing images and detecting patterns with impressive accuracy. This raises important questions: Will we need fewer radiologists? Could AI replace them entirely? And how will the role of the radiologist evolve?
This talk offers a radiologist’s perspective on these pressing issues and shares a personal vision of how radiology might advance in the near future.