Investigating Predictors of Cognitive Decline Using Machine Learning.

Journal: The journals of gerontology. Series B, Psychological sciences and social sciences
Published Date: Mar 9, 2020

Abstract

OBJECTIVES: Genetic risks for cognitive decline are not modifiable; however their relative importance compared to modifiable factors is unclear. We used machine learning to evaluate modifiable and genetic risk factors for Alzheimer's disease (AD), to predict cognitive decline.

Authors

  • Ramon Casanova
    Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
  • Santiago Saldana
    Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
  • Michael W Lutz
    Department of Neurology, Duke University Medical Center, Durham, North Carolina.
  • Brenda L Plassman
    Department of Neurology, Duke University Medical Center, Durham, North Carolina.
  • Maragatha Kuchibhatla
    Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC.
  • Kathleen M Hayden
    Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, USA.

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