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A Bayesian Approach to the Detection of Acute Disorders in a Respiratory Intensive Care Unit

  • Robert B. Fraser
  • Stephen Z. Turney
Conference paper
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 45)

Abstract

Acute pulmonary and systemic disorders occur in mechanically ventilated intensive care patients frequently enough to be of concern. We selected twelve routinely monitored parameters in order to detect certain of these acute disorders (specifically, pneumothorax, pulmonary embolism, ARDS, and sepsis) before they lead to obvious clinical distress. A systematic approach to early detection utilizing changes in the twelve parameters was developed using the sequential Bayesian method. Fifty patients were monitored over a period of one to several days. Six of these patients developed one of the four disorders under study as determined by conventional diagnostic means, such as by x-ray. An examination of the records of these six patients over the time period prior to the actual diagnosis showed that the disorders of three of these six would have been predicted by our Bayesian approach.

Keywords

Systemic Disorder Adult Respiratory Distress Syndrome Intensive Care Patient Emergency Medical Service System Actual Diagnosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Robert B. Fraser
    • 1
  • Stephen Z. Turney
    • 2
  1. 1.Northwest Research Associate, Inc.BellevueUSA
  2. 2.Maryland Institute for Emergency Medical Services SystemsBaltimoreUSA

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