Study: Artificial intelligence program identifies linguistic markers that predict, with 70% accuracy, who gets Alzheimer ’s Disease years later

Fig. 3. Cookie-theft picture description task (CTT) examples from the Framingham Heart Study, including an unimpaired sample (a), an impaired sample (b), and an even more impaired sample showing significant misspellings and minimal grammatic complexity ©. Credit: Eyigoz et al (2020) Alzheimer’s Prediction May Be Found in Writing Tests (The New York Times): … the researchers looked at a group of 80 men and women in their 80s — half had Alzheimer’s and the others did not. But, seven and a half years earlier, all had been cognitively normal. The men and women were participants in the Framingham Heart Study, a long-running federal research effort that requires regular physical and cognitive tests. As part of it, they took a writing test before any of them had developed Alzheimer’s that asks subjects to describe a drawing of a boy standing on an unsteady stool and reaching for a cookie jar on a high shelf while a woman, her back to him, is oblivious to an overflowing sink. The researchers examined the subjects’ word usage with an artificial intelligence program that looked for subtle differences in language. It identified one group of subjects who were more repetitive in their word usage at that earlier time when all of them were cognitively normal. These subjects also made errors, such as spelling words wrongly or inappropriately capitalizing them, and they used telegraphic language, meaning language that has a simple grammatical structure and is missing subjects and...
Source: SharpBrains - Category: Neuroscience Authors: Tags: Brain/ Mental Health Technology & Innovation Alzheimers-disease artificial intelligence biomarker clinical-diagnosis cognitive decline Cognitive-tests cognitively dementia Framingham Heart Study impairment linguistic analysis MCI Source Type: blogs