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DOI: 10.1055/s-0038-1634774
DYNASCENE: An Approach to Computer-Based Intelligent Cardiovascular Monitoring Using Sequential Clinical “Scenes”
Authors
This research is supported in part by NIH grants T1S LM070S6 and R01 LM04336 from the National Library of Medicine and by a grant from the Ira DeCamp Foundation. The authors would like to thank Jeffrey Clyman, M. D. who provided a valuable review of an early draft of this manuscript, and Dean F. Sittig, Ph. D. who helped prepare data for DYNASCENE testing. This paper is an extended version of a paper presented at the Thirteenth Annual Symposium on Computer Applications in Medical Care (SCAMC XIII, Washington, D. C), published with permission.
Publication History
Publication Date:
06 February 2018 (online)
Abstract
Hemodynamic abnormalities such as hypovolemia typically progress through a sequence of discrete clinical phases or “scenes” (e. g., intravascular volume depletion, vasoconstriction, hypotension). Each scene can be defined by a cluster of hemodynamic trends. A natural approach to modeling the process of hemodynamic monitoring involves identifying these scenes and the temporal relationships among them. This approach has been utilized in the development of DYNASCENE, a parallel programming implementation of a computer-based intelligent hemodynamic monitor. This paper discusses: (1) The rationale for utilizing sequential clinical scenes to represent knowledge of hemodynamic behavior, (2) the design of the DYNASCENE system, and (3) preliminary tests of the DYNASCENE system.
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