An algorithm that learns signatures from clinical data, genes, and magnetic resonance imaging (MRI) can help forecasting if someone’s cognitive faculties are prone to deteriorate towards Alzheimer’s in the next five years. This artificial intelligence (AI) algorithm was designed by Dr. Mallar Chakravarty, a computational neuroscientist at the Douglas Mental Health University Institute, and his colleagues from the University of Toronto and the Centre for Addiction and Mental Health.
“At the moment, there are limited ways to treat Alzheimer’s and the best evidence we have is for prevention. Our AI methodology could have significant implications as a ‘doctor’s assistant’ that would help stream people onto the right pathway for treatment. For example, one could even initiate lifestyle changes that may delay the beginning stages of Alzheimer’s or even prevent it altogether,” says Chakravarty, an Assistant Professor in McGill University’s Department of Psychiatry.
To develop the algorithm, the team of researchers used data from the Alzheimer’s Disease Neuroimaging Initiative. The development, published in PLOS Computational Biology, included more than 800 individuals ranging from normal healthy seniors to those experiencing mild cognitive impairment, and Alzheimer’s disease patients.
“We are currently working on testing the accuracy of predictions using new data. It will help us to refine predictions and determine if we can predict even farther into the future,” says Chakravarty. With more data, the scientists would be able to better identify those in the population at greatest risk for cognitive decline leading to Alzheimer’s.
Source: Science Daily