Scottish researchers are making significant strides in the early detection of dementia using artificial intelligence and eye scans. The NeurEYE research team, led by the University of Edinburgh in collaboration with Glasgow Caledonian University, is developing an innovative AI tool that could revolutionise how opticians diagnose and predict dementia risk.
The team has collected nearly a million retinal photographs from opticians across Scotland, creating the world’s largest dataset of its kind. This extensive collection will be used to train AI software to detect signs of dementia in the eyes before other symptoms become apparent.
Professor Baljean Dhillon, co-lead of the NeurEYE project and professor of Clinical Ophthalmology at the University of Edinburgh, explained the significance of this approach:
“The eye can tell us far more than we thought possible. The retina holds a whole wealth of information and is a biological barometer of our brain health.”
The AI technology focuses on analysing blood vessels in the eye for potential indicators of dementia. This method could provide a simple yet powerful tool for early diagnosis, as Professor Dhillon noted, “Something very simple like a photograph of a retina can now be harnessed to potentially predict brain change later on in life”
Early detection is crucial in managing dementia, as it allows for earlier intervention and better patient care. With dementia affecting one in 14 people at age 65 and one in six by age 80, according to Dementia UK, this technology could have a significant impact on public health
The researchers are making rapid progress, with plans to have a prototype ready later this year. They aim for a wider rollout to opticians across the UK by 2026
This development showcases the potential of AI in healthcare, particularly in improving diagnostic capabilities and patient outcomes. As the project moves forward, it holds promise not only for individuals at risk of dementia but also for accelerating the development of new treatments. By identifying people at risk earlier, researchers could potentially find those more likely to benefit from clinical trials, enabling better monitoring of treatment responses.
.
