Finding similar patients in a multi-agent environment

Ayman Mansour, Hao Ying, Peter Dews, Yanqing Ji, John Yen, Richard E. Miller, R. Michael Massanari

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

3 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011
DOIs
StatePublished - May 17 2011
Event2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011 - El Paso, TX, United States
Duration: Mar 18 2011Mar 20 2011

Other

Other2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011
CountryUnited States
CityEl Paso, TX
Period3/18/113/20/11

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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    Mansour, A., Ying, H., Dews, P., Ji, Y., Yen, J., Miller, R. E., & Massanari, R. M. (2011). Finding similar patients in a multi-agent environment. In 2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011 [5752003] https://doi.org/10.1109/NAFIPS.2011.5752003