Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks

We present a novel application of LSTM recurrent neural networks to multilabel classification of diagnoses given variable-length time series of clinical measurements. Our method outperforms a strong baseline on a variety of metrics.