A survey on machine and statistical learning for longitudinal analysis of neuroimaging data in Alzheimer's disease.

Journal: Computer methods and programs in biomedicine
Published Date: Jan 20, 2020

Abstract

BACKGROUND AND OBJECTIVES: Recently, longitudinal studies of Alzheimer's disease have gathered a substantial amount of neuroimaging data. New methods are needed to successfully leverage and distill meaningful information on the progression of the disease from the deluge of available data. Machine learning has been used successfully for many different tasks, including neuroimaging related problems. In this paper, we review recent statistical and machine learning applications in Alzheimer's disease using longitudinal neuroimaging.

Authors

  • Gerard Martí-Juan
    BCN Medtech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain. Electronic address: gerard.marti@upf.edu.
  • Gerard Sanroma-Guell
    German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
  • Gemma Piella
    Information and Communication Technologies Department, Universitat Pompeu Fabra, Barcelona, Spain.

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