Machine learning identifies likelihood of developing dementia

Using data from over 15,300 patients in the US, research from Exeter University found that machine learning can accurately tell who will go on to develop dementia within two years of attending a memory clinic.

The technique identifies hidden patterns in the data and learning who is most at risk.  The study, published in JAMA Network Open and funded by 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.

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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.

In the study timeframe between 2005 and 2015, one in ten attendees (1,568) received a new diagnosis of dementia within two years of visiting the memory clinic. The research found that the machine learning model could predict these new dementia cases with up to 92 per cent accuracy, outperforming two existing alternative research methods.