Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements.

Journal: Journal of Alzheimer's disease : JAD
PMID: 38943387

Abstract

BACKGROUND: Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack validation against postmortem AD neuropathological data.

Authors

  • Xiaowei Zhuang
    Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, 89106, USA.
  • Dietmar Cordes
    Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, 89106, USA; Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, 80309, USA. Electronic address: cordesd@ccf.org.
  • Andrew R Bender
    Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA.
  • Rajesh Nandy
    Department of Biostatistics and Epidemiology, School of Public Health, University of North Texas Health Science Center, Fort Worth, TX, USA.
  • Edwin C Oh
    Interdisciplinary Neuroscience PhD Program, University of Nevada, Las Vegas, NV, USA.
  • Jefferson Kinney
    Interdisciplinary Neuroscience PhD Program, University of Nevada, Las Vegas, NV, USA.
  • Jessica Z K Caldwell
    Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA.
  • Jeffrey Cummings
    Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.
  • Justin Miller
    Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA.

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