Predicting and Understanding Unexpected Respiratory Decompensation in Critical Care Using Sparse and Heterogeneous Clinical Data

Predicting and Understanding Unexpected Respiratory Decompensation in Critical Care Using Sparse and Heterogeneous Clinical Data

Hospital intensive care units (ICUs) care for severely ill patients, many of whom require some form of organ support. Clinicians in ICUs are often challenged with integrating large volumes of continuously recorded physiological and clinical data in order to diagnose and treat patients. In this work,...

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Bibliographic Details
Main Authors: Ren, Oliver, Johnson, Alistair Edward William, Lehman, Eric P., Komorowski, Matthieu, Aboab, Jerome Emile Francois Leon, Tang, Fengyi, Shahn, Zach, Sow, Daby, Mark, Roger G, Lehman, Li-wei
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2019
Online Access:https://hdl.handle.net/1721.1/123313

Internet

https://hdl.handle.net/1721.1/123313

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