Modeling Missing Data in Clinical Time Series with RNNs

A simple strategy to cope with missing data in sequential inputs is demonstrated, addressing the task of multilabel classification of diagnoses given clinical time series, and it is shown that for some diseases, what tests are run can be as predictive as the results themselves.