Our research group is focused on the following areas:
Prognosis is the prediction of the future course of a disease or medical condition. It is a key component of clinical decision making. We use a combinaiton of markers from brain imaging and elsewhere to predict the future course of disease.
Causal machine learning is a branch of machine learning that focuses on causal inference. Causal machine learning has the potential to be used in precision medicine to identify the causal factors that influence disease progression. Additionally, caudal modelling is the basis of individualised treatment effect estimation. We believe this will be a key component of medical care in the future.
The goal of is to develop a new classification system for MS that is based on the underlying biological mechanisms of the disease.
This strand of research aims to develop new MRI biomarkers for MS that can be used to monitor disease progression and response to treatment using advanced machine learning techniques.
This strand of research aims to improve the design of new clinical trials for MS and to develop new ways to measure disease progression.
This strand of research aims to develop new ways to protect the privacy of people with MS and to ensure the security of their data. We are also developing new ways to perform research across hospitals by leveraging federated machine learning and blockchain technologies.
We are developing new ways to perform remote clinical trials for MS patients, thus enabling the inclusion of patients who are unable to travel to a hospital for treatment or who live in remote areas or those whose disability is too severe to travel.
Our group collaborates with other research groups in the UK and internationally to develop new technologies for MS. We are also working with the NHS to develop new ways to deliver care to patients with MS.