Artificial intelligence could one
day change the lives of people facing an Alzheimer’s diagnosis, according to a
new study by researchers at UC, San Francisco. They fed a common type of brain
scans to a machine-learning algorithm, and it learned to diagnose early-stage
Alzheimer’s disease about six years before a clinical diagnosis could be made.
The AI’s diagnostic skills could give doctors a much-needed head start on
treating the degenerative disease. They focused on PET scans that monitored
glucose levels across the brain, because glucose is the primary source of fuel
for brain cells. Once the cells become diseased, they eventually stop using
glucose, making it an important level to track.
Researchers trained the algorithm
on PET scans from patients who were eventually diagnosed with either
Alzheimer’s disease, mild cognitive impairment, or no disorder. The algorithm
began to figure out how to predict Alzheimer’s disease. Eventually, it was able
to correctly identify 92% of patients who developed Alzheimer’s disease in the
first test set and 98% in the second test set, making correct predictions on
average 75.8 months (for the math-impaired, that’s almost six years) before the
patient received an Alzheimer’s diagnosis. While the algorithm isn’t quite
ready for clinical use, it could eventually help doctors start treating
patients much earlier.
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