With no cure and no straightforward way of diagnosing the disease, scientists are exploring every avenue when it comes to detecting Alzheimer’s during its early stages.
One group of researchers has turned its attention to subtle differences in the language of sufferers, and have developed an AI tool they say can pick up on these as a way of potentially screening for the disease.
“Language deficits occur in eight to 10 percent of individuals in the early stages of Alzheimer’s disease, and become more severe and numerous during its later stages,” lead author of the study, K.P. Subbalakshmi explains to New Atlas.
Subbalakshmi and her students set out to develop an AI tool that could detect these language differences, by turning to a standard picture description task currently used in language screening for Alzheimer’s.
Over time, this enabled the algorithm to learn to distinguish between the sentences spoken by healthy subjects and Alzheimer’s sufferers with more than 95-percent accuracy, according to the team.
“We’re opening an exciting new field of research, and making it far easier to explain to patients why the AI came to the conclusion that it did, while diagnosing patients. This addresses the important question of trustability of AI systems in the medical field.”
From here, the team hopes to expand the tool for use in languages other than English, and even enable it to diagnose Alzheimer’s using other types of text, such as an email or social media post.
The researchers also see great potential in using it to track how the disease progresses over time, as a way of detecting it in its very early stages.
“That is, a dataset that tracks patient’s language abilities as time progresses. This will help us develop personalized detection for individuals that are at risk of developing this disease.”
The researchers presented their research at last month’s 19th International Workshop on Data Mining in Bioinformatics.