Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.

Journal: Journal of neuroscience methods
PMID: 29174020

Abstract

BACKGROUND: We present our results in the International challenge for automated prediction of MCI from MRI data. We evaluate the performance of MRI-based neuromorphometrics features (nMF) in the classification of Healthy Controls (HC), Mild Cognitive Impairment (MCI), converters MCI (cMCI) and Alzheimer's Disease (AD) patients.

Authors

  • Patricio Andres Donnelly-Kehoe
    Multimedia Signal Processing Group - Neuroimage Division, French-Argentine International Center for Information and Systems Sciences (CIFASIS) - National Scientific and Technical Research Council (CONICET), 27 de Febrero 210 bis, Rosario, Argentina. Electronic address: patricio.donnelly@gmail.com.
  • Guido Orlando Pascariello
    Multimedia Signal Processing Group - Neuroimage Division, French-Argentine International Center for Information and Systems Sciences (CIFASIS) - National Scientific and Technical Research Council (CONICET), 27 de Febrero 210 bis, Rosario, Argentina.
  • Juan Carlos Gómez
    Multimedia Signal Processing Group - Neuroimage Division, French-Argentine International Center for Information and Systems Sciences (CIFASIS) - National Scientific and Technical Research Council (CONICET), 27 de Febrero 210 bis, Rosario, Argentina.

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