AI algorithm accurately predicts Alzheimer’s disease onset
Posted: 5 October 2018 | Drug Target Review | No comments yet
Scientists have developed an algorithm that can more accurately predict cognitive decline that leads to Alzheimer’s disease. Early preventive measures may help delay and even halt the disease’s onset.
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, designed an algorithm that learns signatures from magnetic resonance imaging (MRI), genetics, and clinical data. This algorithm can help predict whether an individual’s cognitive faculties are likely to deteriorate towards Alzheimer’s within the next five years.
Commenting on how the algorithm could positively impact the onset of the disease, Chakravarty, who is an Assistant Professor in McGill University‘s Department of Psychiatry, said: “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.”
The findings used data from the Alzheimer’s Disease NeuroImaging Initiative. The researchers trained their algorithms using data from 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.
Commenting upon whether the predictions could be improved with more data, Chakravarty said: “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”. 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.
According to the Alzheimer Society of Canada, 564,000 Canadians had Alzheimer’s or another form of dementia in 2016. The figure is anticipated to rise to 937,000 within 15 years.
On a global scale, around 50 million people have dementia and the total number is projected to reach 82 million by 2030 and 152 million by 2050, according to the World Health Organization. Alzheimer’s disease, the most common form of dementia, may contribute to 60-70% of cases. Presently, there is no truly effective treatment for this disease.
The paper was published in PLOS Computational Biology.
Related topics
Analysis, Artificial Intelligence, Informatics
Related conditions
Alzheimer’s disease
Related organisations
Centre for Addiction and Mental Health, McGill University, Toronto University
Related people
Dr Mallar Chakravarty
