A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum.

Journal: Journal of Alzheimer's disease : JAD
Published Date: Jan 1, 2022

Abstract

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transitional condition between healthy aging and dementia. No reliable biomarkers are available to predict the conversion from MCI to AD.

Authors

  • Noemi Massetti
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Mirella Russo
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Raffaella Franciotti
    Department of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Davide Nardini
    Biomedical Unit, ASC 27 s.r.l., Rome, Italy.
  • Giorgio Maria Mandolini
    Biomedical Unit, ASC 27 s.r.l., Rome, Italy.
  • Alberto Granzotto
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Manuela Bomba
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Stefano Delli Pizzi
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Alessandra Mosca
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Reinhold Scherer
  • Marco Onofrj
    University G. d'Annunzio, Chieti, Italy.
  • Stefano L Sensi
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.

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