How is machine learning changing the ways that people could determine whether they have Alzheimer’s?

By | October 21st, 2020

Even before that happens, many people who believe they are at risk will go to their family doctor or a memory specialist to let them know that they’ve noticed changes in their cognition. For example, they can’t remember appointments or how to do simple tasks. Oftentimes, in elderly populations, this is diagnosed first and foremost as geriatric depression because these early signs share a lot of features with this disorder. Certainly what we see in the studies that we’ve done and when we do patient and subject recruitment is a lot of their general practitioners think they have geriatric depression. Slowly, after years have gone by, they realize that they may have memory impairment. Traditionally, most patients will undergo a battery of neuropsychological evaluations once they realize that there is cognitive decline. That doesn’t guarantee they’ll get an Alzheimer’s diagnosis. That just tells you if you’re below average on cognition, or if taken over time, it can reveal your cognition is in decline. It’s only after that, where there’s some suspected dementia, that a doctor will typically prescribe a PET scan or in other cases, a spinal tap, to look for amyloid or tau in the blood.

What we’re trying to do is to say OK, what’s really important is catching these people at the early stages of cognitive decline. We’ve developed an algorithm that takes some simple metrics, like results from tests that are taken in the clinic routinely, looking at whether people have certain copies of a genetic variant called ApoE and some MRI data. We take that data and feed it into our algorithm to predict whether you’re at a high risk for decline or not.

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