Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?

Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
PMID: 39887916

Abstract

INTRODUCTION: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict cognitive worsening.

Authors

  • Mirella Russo
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.
  • Davide Nardini
    Biomedical Unit, ASC 27 s.r.l., Rome, Italy.
  • Sara Melchiorre
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Consuelo Ciprietti
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Gaetano Polito
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Miriam Punzi
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Fedele Dono
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Matteo Santilli
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Astrid Thomas
    Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Stefano L Sensi
    Center for Advanced Studies and Technology - CAST, University G. d'Annunzio of Chieti-Pescara, Italy.

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