An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.

Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
PMID: 39868506

Abstract

INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.

Authors

  • Teresa Filshtein Sönmez
    Department of Public Health Sciences, University of California, Davis, Davis, California, USA.
  • Danielle J Harvey
    Department of Public Health Sciences, University of California-Davis, Davis, CA, USA.
  • Laurel A Beckett
    Department of Public Health Sciences, University of California, Davis, Davis, California, USA.

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