AI Algorithm Predicts Alzheimer's Risk Up to 7 Years Early with 72% Accuracy Using Electronic Health Records
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Researchers at UCSF developed an AI algorithm that can predict Alzheimer's disease risk up to 7 years in advance with 72% accuracy.
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The AI models use data from electronic health records of nearly 3,000 Alzheimer's patients to identify predictors like high cholesterol, prostate issues, and osteoporosis.
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The models connect clinical data to biological reasons for predictors using a precision medicine database tool called SPOKE.
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Key Alzheimer's risk genes like APOE4 were validated by the models. New connections were found like osteoporosis as a predictor in women.
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Early prediction enables interventions to potentially prevent up to a third of Alzheimer's cases through lifestyle changes.