New artificial intelligence research has demonstrated the predictive capability of AI to determine in advance who is likely to develop dementia.
Scientists used artificial intelligence techniques and big data to develop an algorithm capable of recognizing the signatures of dementia two years before its onset, using a single amyloid PET scan of the brain of patients at risk of developing Alzheimer’s disease. Their findings appear in a new study published in the journal Neurobiology of Aging.
Scientists have long known that a protein known as amyloid accumulates in the brain of patients with mild cognitive impairment (MCI), a condition that often leads to dementia. Though the accumulation of amyloid begins decades before the symptoms of dementia occur, this protein couldn’t be used reliably as a predictive biomarker because not all MCI patients develop Alzheimer’s disease.
To conduct their study, the researchers drew on data available through the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a global research effort in which participating patients agree to complete a variety of imaging and clinical assessments.
The researchers used hundreds of amyloid PET scans of MCI patients from the ADNI database to train the team’s algorithm to identify which patients would develop dementia, with an accuracy of 84%, before symptom onset.
While new software has been made available online to scientists and students, physicians won’t be able to use this tool in clinical practice before certification by health authorities.
Paper: “Identifying incipient dementia individuals using machine learning and amyloid imaging”
Reprinted from materials provided by McGill University.