Available
Project number:
2025_98
Start date:
October 2025
Project themes:
Main supervisor:
Senior Lecturer in Health Services Research and Population Health Sciences
Co-supervisor:
Dr Iain Marshall
Additional Information:
Using Artificial Intelligence to Predict Long-term Stroke Outcome from Combined Imaging and Clinical Data
Background
Stroke is a leading cause of death and disability globally. Providing better information on the risks of health outcomes like disability or impaired cognitive function after a stroke is a priority for stroke researchers and people affected by stroke.
Novelty and Importance
All stroke patients admitted to hospital in the UK will undergo brain imaging scans soon after admission to inform diagnosis and treatment. Features found on brain scans have been associated with worsened stroke outcome; in particular tissue hypoattenuation, large lesion size, swelling, hyper-attenuated artery, atrophy and leukoariosis. However, these features represent only a tiny fraction of the wealth of data captured by routine imaging. Artificial Intelligence (AI) based image analysis methods have the potential to phenotype both the stroke and the overall health of a patient’s brain in tremendous detail and so provide invaluable information to better understand the risk of health outcomes following stroke. These models could then be implemented into clinical care alongside the broader patient data to optimise risk prognostication and inform treatment decision making.
Aims and objectives
1. Create a linked database including routinely collected brain Imaging from two South London hospitals linked to structured data from the South London Stroke Register of over >8000 patients
2. Use the created database to develop prediction models (eg Bayesian Inference Models, Generative Adversarial Networks) for complications and outcomes after acute stroke (mortality, stroke recurrence, disability, cognitive impairment)
3. Investigate the utility of adding AI based imaging analysis to conventional statistical modelling
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 30 January 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in March 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at
