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.
Key-Words
Expert Systems - Computer-Assisted Diagnosis - Knowledge Representation - Real-Time
Systems