Artificial intelligence can predict which people who attend memory clinics will develop dementia within two years, research suggests.
According to the study, new dementia cases could be predicted with up to 92% accuracy, far better than two existing alternative research methods.
University of Exeter researchers used data from 15,300 patients in the US, and found that a form of artificial intelligence (AI) called machine learning can tell who will go on to develop dementia.
The technique works by spotting hidden patterns in the data and learning who is most at risk.
The researchers also suggest the algorithm could help reduce the number of people who are falsely diagnosed with dementia.
Professor David Llewellyn, an Alan Turing fellow based at the University of Exeter, who oversaw the study, said: “We’re now able to teach computers to accurately predict who will go on to develop dementia within two years.
“We’re also excited to learn that our machine-learning approach was able to identify patients who may have been misdiagnosed.
“This has the potential to reduce the guesswork in clinical practice and significantly improve the diagnostic pathway, helping families access the support they need as swiftly and as accurately as possible.”
Between 2005 and 2015, one in 10 attendees (1,568) at the memory clinic received a new diagnosis of dementia within two years of their visit.
The researchers also found for the first time that around 8% (130) of the dementia diagnoses appeared to be made in error, as the diagnosis was subsequently reversed.
According to the study, published in JAMA Network Open and funded by Alzheimer’s Research UK, machine-learning models accurately identified more than 80% of these inconsistent diagnoses.
The research suggests AI can not only accurately predict who will be diagnosed with dementia, but has the potential to improve the accuracy of the diagnoses.
Machine learning works by using patient information routinely available in the clinic, such as memory and brain function, performance on cognitive tests and specific lifestyle factors.
The team plans follow-up studies to evaluate the practical use of the machine-learning method in clinics, to assess whether it can be rolled out to improve diagnosis, treatment and care.
The researchers analysed data from people who attended a network of 30 National Alzheimer’s Coordinating Centre memory clinics in the US.
The attendees did not have dementia at the start of the study, though many were experiencing problems with memory or other brain functions.
Dr Rosa Sancho, head of research at Alzheimer’s Research UK, said: “Artificial intelligence has huge potential for improving early detection of the diseases that cause dementia and could revolutionise the diagnosis process for people concerned about themselves or a loved one showing symptoms.
“This technique is a significant improvement over existing alternative approaches and could give doctors a basis for recommending lifestyle changes and identifying people who might benefit from support or in-depth assessments.”