From clinical trials to in-silico trials: virtual twins, virtual chimeras, and not a patient in sight 
Zeike Taylor (Associate Professor School of Mechanical Engineering)

New medical devices must successfully pass through clinical trials before they can be certified for use. These trials are very expensive and lengthy, and necessarily limited in scope. Some advocate a new approach, called in-silico trials, in which we create cohorts of virtual patients, virtually implant a digital replica of the device in each, and predict its performance at any point from then on. In this talk, I will briefly describe how in-silico trials can be realised in practice, summarise their potential benefits, and touch on their limitations and the gaps that still need to be filled.

Your eyes are windows to your heart
Nishant Ravikumar (Lecturer in Computer Science)

Recent advances in Machine Learning have opened the doors to significantly improving the quality of healthcare delivered to patients worldwide. Ranging from early identification of patients at risk of developing diseases in the future to designing personalised treatment strategies, machine learning is steadily transforming the patient care pathway. In this talk I will describe current efforts underway at the University of Leeds to help identify patients at risk of cardiovascular disease, using multi-modal, multi-organ data, in a cost-effective manner.