AI Algorithm Uses Key Signatures to Predict Onset of AD
By MedImaging International staff writers Posted on 15 Oct 2018 |
A team of researchers has designed an artificial intelligence (AI) algorithm that learns signatures from magnetic resonance imaging (MRI), genetics, and clinical data to accurately predict cognitive decline leading to Alzheimer’s disease. The algorithm can help predict whether an individual’s cognitive faculties are likely to deteriorate towards Alzheimer’s in the next five years.
The researchers trained the algorithm by using data of more than 800 people ranging from normal healthy seniors to those experiencing mild cognitive impairment, and Alzheimer’s disease patients. They replicated their results within the study on an independently collected sample from the Australian Imaging and Biomarkers Lifestyle Study of Ageing. Using more data, the scientists will now be able to better identify those in the population at greatest risk for cognitive decline leading to Alzheimer’s.
“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,” said Dr. Mallar Chakravarty, a computational neuroscientist at the Douglas Mental Health University Institute and Assistant Professor in McGill University’s Department of Psychiatry. “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.”
The researchers trained the algorithm by using data of more than 800 people ranging from normal healthy seniors to those experiencing mild cognitive impairment, and Alzheimer’s disease patients. They replicated their results within the study on an independently collected sample from the Australian Imaging and Biomarkers Lifestyle Study of Ageing. Using more data, the scientists will now be able to better identify those in the population at greatest risk for cognitive decline leading to Alzheimer’s.
“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,” said Dr. Mallar Chakravarty, a computational neuroscientist at the Douglas Mental Health University Institute and Assistant Professor in McGill University’s Department of Psychiatry. “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.”
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