Estimating patient's health state using latent structure inferred from clinical time series and text

Estimating patient's health state using latent structure inferred from clinical time series and text

Modern intensive care units (ICUs) collect large volumes of data in monitoring critically ill patients. Clinicians in the ICUs face the challenge of interpreting large volumes of high-dimensional data to diagnose and treat patients. In this work, we explore the use of Hierarchical Dirichlet Processe...

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Bibliographic Details
Main Authors: Zalewski, Aaron D. (Contributor), Long, William J (Contributor), Johnson, Alistair Edward William (Contributor), Mark, Roger G (Contributor), Lehman, Li-Wei (Contributor)
Other Authors: Institute for Medical Engineering and Science (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2017-12-19T20:13:30Z.
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