A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.

Journal: Neurology
PMID: 40132145

Abstract

BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do not show cognitive decline over 80 weeks of follow-up. Identifying and excluding these individuals can increase power to detect treatment effects. We aimed to develop machine learning-based predictive models to identify persons unlikely to show decline on placebo treatment over 80 weeks.

Authors

  • Bhargav T Nallapu
    Saul B. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, NY.
  • Kellen K Petersen
    Department of Neurology, Washington University in St. Louis, MO.
  • Tianchen Qian
    Department of Statistics, University of California Irvine.
  • Idris Demirsoy
    Department of Computer Science, University in Uşak, Turkey.
  • Elham Ghanbarian
    Department of Neurology, University of California Irvine; and.
  • Christos Davatzikos
    Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Richard B Lipton
    Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA.
  • Ali Ezzati
    Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA.

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