This theme is primarily supported by our Organisations, Information and Knowledge (OAK) and Complex Systems Modelling (CSM) groups, with input from the Machine Learning group.
Research in this theme is driven by the complexity of the clinical setting, aligned with challenges in harnessing technology to deliver healthcare more effectively.
Research is further supported by a network of clinical and interdisciplinary collaborations provided by:
News and highlights
Chatbots could be used to deliver psychotherapy during Covid-19 and beyond
The study, led by Dr Matthew Bennion from the University’s Department of Computer Science, argues that chatbots are an under-used resource and could be used to help more people talk through their issues.
Department is part of a new EU consortium researching solutions for speech problems
The Department of Computer Science is part of a European-wide project which aims to transform the well-being of people with debilitating speech problems.
Researchers develop Artificial Intelligence to prevent new waves of COVID-19
A University of Sheffield research student has helped develop Artificial Intelligence (AI) to predict COVID-19 from standard blood tests two weeks earlier than current, existing tests.
Speech and language technology in healthcare
Researchers in the Speech and Hearing group are investigating ways of using audio and speech technology to improve the physical and mental wellbeing of people.
Computational models in healthcare
Professor Richard Clayton has had a long running interest in developing computational models to investigate the mechanisms that initiate and sustain dangerous disorders of heart rhythm in the human heart, and this has been funded through grants and fellowships from the British Heart Foundation.
Professor Clayton is currently working on a UKRI funded project which is looking to address: Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models
Developing cell-based simulation of tumour growth
A team in the Department of Computer Science and Insigneo Institute at the University of Sheffield, lead by Dr Dawn Walker and Dr Paul Richmond, are developing a cell-based simulation of the growth of the tumours. The agent-based model can represent potentially millions of individual neuroblastoma cells which can either grow and divide, or die depending on their local environment (e.g. oxygen level, presence of chemotherapy drugs). The model feeds into a higher-level virtual representation of the tumour developed by collaborators across Europe, and is accelerated using the FLAME GPU2 framework developed by Dr Richmond's Research Software Engineering team. This allows the tumours of individual patients and the outcome of their treatments to be simulated in a reasonable amount of time.
The PRIMAGE project is devoted to developing methods of computational analysis of medical images applied to childhood cancer.