Quantitative Longitudinal Predictions of Alzheimer's Disease by Multi-Modal Predictive Learning.

Journal: Journal of Alzheimer's disease : JAD
Published Date: Jan 1, 2021

Abstract

BACKGROUND: Quantitatively predicting the progression of Alzheimer's disease (AD) in an individual on a continuous scale, such as the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) scores, is informative for a personalized approach as opposed to qualitatively classifying the individual into a broad disease category.

Authors

  • Mithilesh Prakash
    University of Eastern Finland, A.I. Virtanen Institute for Molecular Sciences, Kuopio, Finland.
  • Mahmoud Abdelaziz
    Zewail City of Science and Technology, Giza, Egypt.
  • Linda Zhang
    Department of Biomedical Informatics, Vanderbilt University, 2525 West End Ave, Suite 14113, Nashville, TN, 37203, USA. linda.zhang92@vanderbilt.edu.
  • Bryan A Strange
    Department of Neuroimaging, Alzheimer's Disease Research Centre, Reina Sofia-CIEN Foundation, Madrid, Spain.
  • Jussi Tohka
    Department of Bioengineering and Aerospace Engineering, Universidad Carlos III de Madrid, Leganes, Spain; Instituto de Investigación Sanitaria Gregorio Marañon, Madrid, Spain; University of Eastern Finland, AI Virtanen Institute for Molecular Sciences, Kuopio, Finland.

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