The MuM-PreDiCT project has been successful in the funding call from the Strategic Priorities Fund (SPF): Tackling multimorbidity at scale: Understanding disease clusters, determinants & biological pathways.

This Strategic Priorities Fund (SPF) initiative, is jointly funded by the UKRI – MRC and the Department of Health and Social Care (DHSC), through the National Institute for Health Research (NIHR).

The project will study and improve maternity care for women who are also managing two or more long-term health conditions. These can be both physical conditions, such as diabetes and raised blood pressure, and mental health conditions such as depression and anxiety.

Our research team will develop statistical machine learning methods to analyse electronic health records from across all four nations comprising the UK. We will find out how many women have two or more long-term health conditions that presented before pregnancy and what health conditions they have. We will try and identify if factors such as age, weight, cultural or social background, level of education and number of previous pregnancies influences this. We will also find out which health conditions group together (cluster) during pregnancy, which clusters are most common and whether some clusters affect some women more than others.

Christopher Yau
Professor of Artificial Intelligence

I am Professor of Artificial Intelligence. I am interested in statistical machine learning and its applications in the biomedical sciences.