Using AI to better understand multiple long-term conditions

Researchers at the University of Southampton are to lead a new study using artificial intelligence to help understand multiple long-term conditions.

The study carried out with researchers at the University of Oxford, will use machine learning to identify clusters of diseases on the basis of social factors, such as mobility and finances, as well as health and biological markers.

The information will be used to understand the health and social care needs of people within each cluster over time and develop tailored treatment approaches that join up health and social care. It is being led by Dr Hajira Dambha-Miller, a GP and an NIHR Clinical Lecturer in Primary Care within the Faculty of Medicine.

The project is part of a series of studies and collaborations, funded by £12million from the NIHR, which are using advanced data science and artificial intelligence methods to identify and understand clusters of multiple long-term conditions and develop ways to prevent and treat them.

An estimated 14 million people in England are living with two or more long-term conditions, with two-thirds of adults aged over 65 expected to be living with multiple long-term conditions by 2035.

People who develop multiple long-term conditions often do not have a random assortment of diseases but rather a largely predictable cluster of conditions. Developing a better understanding of these disease clusters, including how they develop over the course of a person’s life and are influenced by wider determinants of health, requires novel research and analytical tools that can operate across complex datasets.