Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models

This is the source code used in the following paper: Ullah, S., Xu, Z., Wang, H., Menzel, S., Sendhoff, B., "Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models" 2020 IEEE World Congress on Computational Intelligence This paper investigates the effectiveness of Supplementary Medical Information, for improving the prediction of Variational Recurrent Models in Clinical Time Series Forecasting.

Related Organizations

Leiden University
Netherlands
Honda (Germany)
Germany

Keywords

Clinical Applications, time series forecasting, recurrent neural networks, deep latent-variable models, MIMIC III

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