Decision analytic approach to severe head injury management.

Severe head injury management in the intensive care unit is extremely challenging due to the complex domain, the uncertain intervention efficacies, and the time-critical setting. We adopt a decision analytic approach to automate the management process. We document our experience in building a simpli...

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Main Authors: Harmanec D., Tze-Yun LEONG, Sundaresh S., Poh K., Yeo T., Ng I., Lew T.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1999
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Online Access:https://ink.library.smu.edu.sg/sis_research/3010
https://ink.library.smu.edu.sg/context/sis_research/article/4010/viewcontent/procamiasymp00004_0308.pdf
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spelling sg-smu-ink.sis_research-40102018-07-13T04:35:34Z Decision analytic approach to severe head injury management. Harmanec D., Tze-Yun LEONG, Sundaresh S., Poh K., Yeo T., Ng I., Lew T., Severe head injury management in the intensive care unit is extremely challenging due to the complex domain, the uncertain intervention efficacies, and the time-critical setting. We adopt a decision analytic approach to automate the management process. We document our experience in building a simplified influence diagram that involves about 3000 numerical parameters. We identify the inherent problems in structuring a model with unclear domain relationships, numerous interacting variables, and real-time multiple inputs. We analyze the effectiveness and limitations of the decision analytic approach and present a set of desiderata for effective knowledge acquisition in this setting. We also propose a semi-qualitative approach to parameter elicitation. 1999-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3010 https://ink.library.smu.edu.sg/context/sis_research/article/4010/viewcontent/procamiasymp00004_0308.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Health Information Technology
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer Sciences
Health Information Technology
spellingShingle Computer Sciences
Health Information Technology
Harmanec D.,
Tze-Yun LEONG,
Sundaresh S.,
Poh K.,
Yeo T.,
Ng I.,
Lew T.,
Decision analytic approach to severe head injury management.
description Severe head injury management in the intensive care unit is extremely challenging due to the complex domain, the uncertain intervention efficacies, and the time-critical setting. We adopt a decision analytic approach to automate the management process. We document our experience in building a simplified influence diagram that involves about 3000 numerical parameters. We identify the inherent problems in structuring a model with unclear domain relationships, numerous interacting variables, and real-time multiple inputs. We analyze the effectiveness and limitations of the decision analytic approach and present a set of desiderata for effective knowledge acquisition in this setting. We also propose a semi-qualitative approach to parameter elicitation.
format text
author Harmanec D.,
Tze-Yun LEONG,
Sundaresh S.,
Poh K.,
Yeo T.,
Ng I.,
Lew T.,
author_facet Harmanec D.,
Tze-Yun LEONG,
Sundaresh S.,
Poh K.,
Yeo T.,
Ng I.,
Lew T.,
author_sort Harmanec D.,
title Decision analytic approach to severe head injury management.
title_short Decision analytic approach to severe head injury management.
title_full Decision analytic approach to severe head injury management.
title_fullStr Decision analytic approach to severe head injury management.
title_full_unstemmed Decision analytic approach to severe head injury management.
title_sort decision analytic approach to severe head injury management.
publisher Institutional Knowledge at Singapore Management University
publishDate 1999
url https://ink.library.smu.edu.sg/sis_research/3010
https://ink.library.smu.edu.sg/context/sis_research/article/4010/viewcontent/procamiasymp00004_0308.pdf
_version_ 1770572778635788288