Explainable Artificial Intelligence in Ambulatory Digital Dementia Screenings.

Journal: Studies in health technology and informatics
Published Date:

Abstract

Recently, digital apps have entered the market to enable the early diagnosis of dementia by offering digital dementia screenings. Some of these apps use Machine Learning (ML) to predict cognitive impairment. The aim of this work is to find explanations for the predictions of such a mobile application called DemPredict using methods from the field of Explainable Artificial Intelligence (XAI). In order to evaluate which method is best suited, different XAI approaches are used and compared. However, the comparability of the results is a key challenge. By evaluating the trustworthiness, stability, and computation time of the methods, it is possible to identify the optimal XAI approaches for the respective algorithms.

Authors

  • Markus Schinle
    FZI Research Center for Information Technologies, Germany.
  • Christina Erler
    FZI Research Center for Information Technologies, Germany.
  • Maximilian Hess
    FZI Research Center for Information Technologies, Germany.
  • Wilhelm Stork
    FZI Forschungszentrum Informatik, Karlsruhe.