Attention-based Time-aware Recurrent Neural Network for Predicting Clinical Outcomes in Electronic Health Records

The authors propose two interpretable deep learning architectures, TA-RNN and TA-RNN-AE, that leverage time embedding and dual-level attention mechanisms to predict clinical outcomes in electronic health records at the next visit and multiple visits ahead, respectively.