Time-aware long short-term memory

{{More citations needed|date=April 2018}}

Time-aware LSTM (T-LSTM) is a long short-term memory (LSTM) unit capable of handling irregular time intervals in longitudinal patient records. T-LSTM was developed by researchers from Michigan State University, IBM Research, and Cornell University and was first presented in the Knowledge Discovery and Data Mining (KDD) conference.{{cite web|url=http://www.kdd.org/kdd2017/papers/view/patient-subtyping-via-time-aware-lstm-networks|title=Patient Subtyping via Time-Aware LSTM Networks|first=KDD|last=Organizers|website=www.kdd.org}}

Experiments using real and synthetic data proved that T-LSTM auto-encoder outperformed widely used frameworks including LSTM and MF1-LSTM auto-encoders.{{Citation needed|date=April 2018}}