Incremental Value of Multidomain Risk Factors for Dementia Prediction: A Machine Learning Approach.

Journal: The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
PMID: 39209617

Abstract

OBJECTIVE: The current evidence regarding how different predictor domains contributes to predicting incident dementia remains unclear. This study aims to assess the incremental value of five predictor domains when added to a simple dementia risk prediction model (DRPM) for predicting incident dementia in older adults.

Authors

  • Wei Ying Tan
    Saw Swee Hock School of Public Health (WYT, SH), National University of Singapore and National University Health System, Singapore.
  • Carol Anne Hargreaves
    Office of the President (CAH), National University of Singapore, Singapore.
  • Gavin S Dawe
    Healthy Longevity Translational Research Programme (GSD), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Precision Medicine Translational Research Programme (GSD), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Neurobiology Programme (GSD), Life Sciences Institute, National University of Singapore, Singapore; Department of Pharmacology (SH), Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Wynne Hsu
    School of Computing, National University of Singapore.
  • Mong Li Lee
    School of Computing, National University of Singapore.
  • Ashwati Vipin
    Dementia Research Centre (AV, NK), Lee Kong Chian School of Medicine, Singapore.
  • Nagaendran Kandiah
    Dementia Research Centre, Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Level 18 308232, Singapore.
  • Saima Hilal
    Memory Aging and Cognition Centre, National University Health System, Singapore, Singapore.

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