A Self-Adaptively Evolutionary Screening Approach for Sepsis Patient

Yu Jiang, Pengliu Tan, Houbing Song, Binhua Wan, Mohammad Hosseini, Lui Sha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Today, sepsis syndrome is one of the leading cause of death globally, and is of great clinical importance. In this paper, we present a self-adaptively evolutionary sepsis screening system to shorten the time of syndrome detection and improve the positive effect of treatment, with the screening frequency and content can be automatically adjusted according to the current status of the patient. First, we propose a novel graphical computation model named AdapDBN with a clearly defined syntax for the medical knowledge presentation, especially for the presentation of the pathophysiology model of the disease. Then, the semantics of AdapDBN is formally defined for the evolutionary inference of syndrome onset probability. Finally, we demonstrate how to initialize AdapDBN with sepsis-related epidemiologic statics, published clinical research and physician's knowledge and how to incorporate it into existing sepsis screening and decision support flow. We evaluate its effectiveness and superiority with comparisons to existing computation techniques.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages60-65
Number of pages6
ISBN (Electronic)9781467390361
DOIs
StatePublished - Aug 16 2016
Event29th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2016 - Belfast, Ireland
Duration: Jun 20 2016Jun 23 2016

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
Volume2016-August
ISSN (Print)1063-7125

Other

Other29th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2016
Country/TerritoryIreland
CityBelfast
Period6/20/166/23/16

Keywords

  • Adaptively
  • Dynamic Bayesian Network
  • Sepsis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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