Medical multivariate time series imputation and forecasting based on a recurrent conditional Wasserstein GAN and attention.

Journal: Journal of biomedical informatics
Published Date:

Abstract

OBJECTIVE: In the fields of medical care and research as well as hospital management, time series are an important part of the overall data basis. To ensure high quality standards and enable suitable decisions, tools for precise and generic imputations and forecasts that integrate the temporal dynamics are of great importance. Since forecasting and imputation tasks involve an inherent uncertainty, the focus of our work lay on a probabilistic multivariate generative approach that samples infillings or forecasts from an analysable distribution rather than producing deterministic results.

Authors

  • Sven Festag
    Department of Medical Informatics, Medical Faculty, RWTH Aachen University.
  • Cord Spreckelsen
    Department of Medical Informatics, Medical Faculty, RWTH Aachen University.