Machine learning model predicts Alzheimer's decline using routine clinic data

Affects 60 million dementia patients worldwide with personalized progression forecasting to improve care planning and family expectations.

For decades, families facing an Alzheimer's diagnosis have been offered only statistical averages where they needed individual answers. Researchers in the United Kingdom have now built machine learning models capable of forecasting a single patient's cognitive and functional decline over the next twelve months — using only the routine assessments already present in every clinic visit. The work suggests that the signal for personalized prognosis has always been there, hidden in the specific things a person can and cannot do, waiting for the right lens to read it.

Machine learning model predicts Alzheimer's decline using routine clinic data

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