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Using AI and machine learning to improve stroke outcomes

April 24th, 2025 Tom Seymour

Artificial intelligence (AI) and machine learning is being used to personalize stroke care for patients to try and reduce future disability.

The research project from the University of Exeter, in partnership with the Royal Devon University NHS Foundation Trust and NIHR Applied Research Collaboration South West Peninsula (PenARC), uses AI to help doctors identify patients most likely to benefit from clot-busting treatment. This treatment, known as thrombolysis, can reduce disability caused by stroke when given early.

The project, known as the SAMueL 2 (Stroke Audit Machine Learning project), developed a tool to better understand how clot-busting drugs are used in hospitals and to help improve their use so more patients receive the best available treatment as quickly as possible.

This represents the world's first integration of AI into a national stroke audit and is set to make a big difference to how hospitals deliver thrombolysis care, ensuring that treatment is targeted more effectively for local populations.

Professor Martin James, Consultant Stroke Physician and Honorary Clinical Professor at the University of Exeter Medical School, said, "SAMueL analysis includes nationwide data from a quarter of a million stroke cases, and by using this data, we can provide each hospital with a tailored target for thrombolysis. When teams have used this as a benchmark, they've been able to treat more patients, more effectively.

"Stroke has a life-changing impact, so it's inspiring to see how research like this can lead to more personalized, faster treatment and better outcomes for patients and their families."

Stroke is a leading cause of death and disability with more than 100,000 people hospitalized in the U.K. each year. One way of treating stroke and preventing disability is to give a patient medication to break down blood clots. This treatment has been given to approximately 11% of patients in recent years, including over 1,000 patients per year in the South West.

However, thrombolysis isn't suitable for every patient and is only effective if given quickly after a stroke. How often thrombolysis is used, and how quickly it is given, can vary widely across the country.

Building on previous research, the research team used computer models to study why thrombolysis use varies between hospitals. They also worked to predict patient outcomes and identify which patient characteristics most influence recovery after a stroke, both with and without thrombolysis.

For more information about SAMueL, please visit the PenARC website: https://arc-swp.nihr.ac.uk/research/projects/samuel-2/.

Provided by University of Exeter

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