Interpretable machine learning for dementia: A systematic review.

Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association
Published Date: Feb 3, 2023

Abstract

INTRODUCTION: Machine learning research into automated dementia diagnosis is becoming increasingly popular but so far has had limited clinical impact. A key challenge is building robust and generalizable models that generate decisions that can be reliably explained. Some models are designed to be inherently "interpretable," whereas post hoc "explainability" methods can be used for other models.

Authors

  • Sophie A Martin
    Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Florence J Townend
    Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Frederik Barkhof
    MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands.
  • James H Cole
    Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom.

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