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Finding similar patients in a multi-agent environment

  • Ayman Mansourb(Author)
    ,
  • Hao Yingb(Author)
    ,
  • Peter Dewsd(Author)
    ,
  • Yanqing Jia(Author)
    ,
  • John Yenc(Author)
    ,
  • Richard E. Millere(Author)
  • ,
  • bWayne State University
    ,
  • cPenn State University
    ,
  • dSt. John Health
    ,
  • eVA Medical Center
    ,
  • fResearch for The Critical Junctures Institute
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution

Abstract

Finding similar patients is highly desirable in many clinical applications. In this paper, we address the issue of how to find similar patients in a multi-agent environment where software agents, located in different places, work collaboratively and proactively help one another to empower their human users to achieve a common healthcare goal. We show how the agents, equipped with fuzzy similarity rules developed by the physicians on the team, collaborate to find similar patients in each agent's patient database. We describe the architecture, design and implementation of the system. Using the popular agent language JADE and clinical information on 1,000 patients treated at the Detroit Veterans Affairs Medical Center, we have implemented a five-agent system and generated some preliminary simulation results.