A Clinically-Translatable Machine Learning Algorithm for the Prediction of Alzheimer's Disease Conversion in Individuals with Mild and Premild Cognitive Impairment.

Journal: Journal of Alzheimer's disease : JAD
Published Date: Jan 1, 2018

Abstract

BACKGROUND: Available therapies for Alzheimer's disease (AD) can only alleviate and delay the advance of symptoms, with the greatest impact eventually achieved when provided at an early stage. Thus, early identification of which subjects at high risk, e.g., with MCI, will later develop AD is of key importance. Currently available machine learning algorithms achieve only limited predictive accuracy or they are based on expensive and hard-to-collect information.

Authors

  • Massimiliano Grassi
    Medibio Limited, Savage, MN, United States.
  • Giampaolo Perna
    Medibio Limited, Savage, MN, United States.
  • Daniela Caldirola
    Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
  • Koen Schruers
    Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine, and Life Sciences, Research Institute of Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands.
  • Ranjan Duara
    Department of Neurology, Herbert Wertheim College of Medicine, Florida International University of Miami, Miami, FL, USA.
  • David A Loewenstein
    Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, USA.

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