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Long‐term Alzheimer's disease mortality prediction in adults aged ≥60 years: A prospective cohort study benchmarking survival machine learning algorithms
0
Zitationen
11
Autoren
2025
Jahr
Abstract
We benchmarked 10 survival machine learning (ML) algorithms using 116 clinical variables to predict long-term Alzheimer's disease (AD)-specific mortality.Feature importance analysis identified novel non-imaging clinical predictors, including arm circumference, self-rated physical activity, and alcohol consumption.This work highlights the underused potential of routine clinical data for AD mortality prediction and underscores the need for interpretable, population-based ML applications.
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