Artificial intelligence can predict who will develop dementia within two years of attending a memory clinic, according to a new large-scale study published in JAMA Network Open today, Thursday 16th December.
Using data from more than 15,300 patients in the US between 2005 and 2015, researchers from the University of Exeter and The Alan Turing Institute found that one in ten (1,568) of those who attended a clinic received a new diagnosis of dementia within two years of their visit.
The scientists also found that around eight per cent (130) of diagnoses were made in error, as their diagnosis was subsequently reversed. Machine learning models accurately identified more than 80 per cent of these inconsistent diagnoses.
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 life-style changes and identifying people who might benefit from support or in-depth assessments.”
The researchers analysed data from people who attended a network of 30 National Alzheimer’s Coordinating Center 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.
The technique works by spotting hidden patterns in the data and learning who is most at risk. The study, funded by Alzheimer’s Research UK, also suggested that the algorithm could help reduce the number of people who may have been falsely diagnosed with dementia.
Professor David Llewellyn, a Fellow at The Alan Turing Institute 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.”
The team now plans to conduct 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 dementia diagnosis, treatment and care.
