Using Machine Learning to Predict Dementia from Neuropsychiatric Symptom and Neuroimaging Data.

Journal: Journal of Alzheimer's disease : JAD
Published Date: Jan 1, 2020

Abstract

BACKGROUND: Machine learning (ML) is a promising technique for patient-specific prediction of mild cognitive impairment (MCI) and dementia development. Neuropsychiatric symptoms (NPS) might improve the accuracy of ML models but have barely been used for this purpose.

Authors

  • Sascha Gill
    Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
  • Pauline Mouches
    Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
  • Sophie Hu
    Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
  • Deepthi Rajashekar
    Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
  • Frank P MacMaster
    Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
  • Eric E Smith
    Hotchkiss Brain Institute, University of Calgary, Calgary, AB.
  • Nils D Forkert
    Department of Radiology, University of Calgary, Calgary, Canada. nils.forkert@ucalgary.ca.
  • Zahinoor Ismail
    Department of Psychiatry, University of Calgary, Calgary, AB, Canada.

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