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Researchers have discovered how to diagnose Alzheimer's disease with more than 82 per cent accuracy by evaluating the interplay between four linguistic factors; and developing automated technology to detect these impairments.
The study, led by Dr. Frank Rudzicz, Scientist, Toronto Rehab, is published in the December issue of the
Journal of Alzheimer's Disease. The method and automated application of the assessment is proven to be more accurate than the current initial assessment tool used by health-care professionals. It can also provide an objective diagnostic rating for dementia.
"Previous to our study, language factors were connected to Alzheimer's disease, but often only related to delayed memory or a person's ability to follow instructions," says Dr. Rudzicz, who is also assistant professor, Department of Computer Science, University of Toronto and a Network Investigator with the AGE-WELL Network of Centres of Excellence. "This study characterizes the diversity of language impairments experienced by people with Alzheimer's disease, and our automated detection algorithm takes this into account."
Read the full media release here.