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This article has multiple issues. Please help improve it or discuss these issues on the talk page. (Learn how and when to remove these messages) The topic of this article may not meet Misplaced Pages's general notability guideline. Please help to demonstrate the notability of the topic by citing reliable secondary sources that are independent of the topic and provide significant coverage of it beyond a mere trivial mention. If notability cannot be shown, the article is likely to be merged, redirected, or deleted. Find sources: "Time aware long short-term memory" – news · newspapers · books · scholar · JSTOR (April 2018) (Learn how and when to remove this message) This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. Find sources: "Time aware long short-term memory" – news · newspapers · books · scholar · JSTOR (April 2018) (Learn how and when to remove this message) (Learn how and when to remove this message)

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. Experiments using real and synthetic data proved that T-LSTM auto-encoder outperformed widely used frameworks including LSTM and MF1-LSTM auto-encoders.

References

1. Organizers, KDD. "Patient Subtyping via Time-Aware LSTM Networks". www.kdd.org.

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