A multivariate timeseries modeling approach to severity of illness assessment and forecasting in ICU with sparse, heterogeneous clinical data

A multivariate timeseries modeling approach to severity of illness assessment and forecasting in ICU with sparse, heterogeneous clinical data

The ability to determine patient acuity (or severity of illness) has immediate practical use for clinicians. We evaluate the use of multivariate timeseries modeling with the multi-task Gaussian process (GP) models using noisy, incomplete, sparse, heterogeneous and unevenly-sampled clinical data, inc...

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Bibliographic Details
Main Authors: Pimentel, Marco A. F., Clifton, David A., Ghassemi, Marzyeh, Szolovits, Peter, Feng, Mengling, Naumann, Tristan Josef, Brennan, Thomas Patrick
Other Authors: Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Format: Article
Language:en_US
Published: Association for the Advancement of Artificial Intelligence 2017
Online Access:http://hdl.handle.net/1721.1/112992
https://orcid.org/0000-0001-6349-7251
https://orcid.org/0000-0003-2150-1747
https://orcid.org/0000-0001-8411-6403

Internet

http://hdl.handle.net/1721.1/112992
https://orcid.org/0000-0001-6349-7251
https://orcid.org/0000-0003-2150-1747
https://orcid.org/0000-0001-8411-6403

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