Robust parameter extraction for decision support using multimodal intensive care data
Name
Clifford-Robust parameter extraction.pdf
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312.37 KB
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Author(s)
Clifford, Gari D.
Long, William J.
Moody, George B.
Szolovits, Peter
Date Issued
October 2008
Journal
Philosophical Transactions of the Royal Society A Mathematical, Physical and Engineering Sciences
Publisher
The Royal Society
Citation
Clifford, G.D et al. “Robust parameter extraction for decision support using multimodal intensive care data.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367 (2009): 411-429. Web. 1 Dec. 2011. © 2008 The Royal Society
Version
Final published version
Abstract
Digital information flow within the intensive care unit (ICU) continues to grow, with advances in technology and computational biology. Recent developments in the integration and archiving of these data have resulted in new opportunities for data analysis and clinical feedback. New problems associated with ICU databases have also arisen. ICU data are high-dimensional, often sparse, asynchronous and irregularly sampled, as well as being non-stationary, noisy and subject to frequent exogenous perturbations by clinical staff. Relationships between different physiological parameters are usually nonlinear (except within restricted ranges), and the equipment used to measure the observables is often inherently error-prone and biased. The prior probabilities associated with an individual's genetics, pre-existing conditions, lifestyle and ongoing medical treatment all affect prediction and classification accuracy. In this paper, we describe some of the key problems and associated methods that hold promise for robust parameter extraction and data fusion for use in clinical decision support in the ICU.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1098/rsta.2008.0157
