Research

All PhD projects will be associated with one or more of our multidisciplinary themes.

AI-Enabled Diagnostics or Prognostics

Deep learning enables networks to model complex nonlinear relationships and these approaches have found application in clincial diagnosis using either data from electronic health records (like blood test results) or the images produced during radiology exams or in digital pathology suites.

Projects in this theme help us create, initiate and deploy solutions centered on clinical use cases of direct applicability in hospitals. Example projects include the detection of radiological abnormalities; characterisation of tissues and tissue abnormalities (e.g. cancer staging); or predicting a patient’s state from a series of measurement over time.

AI-Enabled Operations

We will seek to create new approaches to investigate and characterise the performance of healthcare systems and processes – such as the flow of patients through emergency departments, or the demand for blood products. These projects, which can often be translated very quickly into real applications, can have significant impacts on the efficiency with which we can deliver care and help improve patients’ outcomes.

AI-Enabled Therapeutics

Our final theme is the use of deep learning and other Artificial Intelligence method in therapeutic inference or even in a therapy itself. Artificial Intelligence methods may be most applicable here in mental health, where deployment of ‘talking therapies’ is as efficacious through the internet or telephony as face-to-face; or in the development of ‘avatar therapies’.