A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition-primed decision model

Yanqing Ji, Hao Ying, John Yen, Shizhuo Zhu, Daniel C. Barth-Jones, Richard E. Miller, R. Michael Massanari

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well-known human decision-making model called Recognition-Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs.

Original languageEnglish (US)
Pages (from-to)827-845
Number of pages19
JournalInternational Journal of Intelligent Systems
Volume22
Issue number8
DOIs
StatePublished - Aug 1 2007

Fingerprint

Intelligent agents
Decision Model
Intelligent Agents
Drugs
Multi agent systems
Decision making
Surveillance
Multi-agent Systems
Fuzzy logic
Decision Making
Unknown
Systems analysis
Inconsistent
Fuzzy Logic
System Design
Latency
Paradigm
Electronics
Generalise
Necessary

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

Cite this

Ji, Yanqing ; Ying, Hao ; Yen, John ; Zhu, Shizhuo ; Barth-Jones, Daniel C. ; Miller, Richard E. ; Massanari, R. Michael. / A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition-primed decision model. In: International Journal of Intelligent Systems. 2007 ; Vol. 22, No. 8. pp. 827-845.
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A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition-primed decision model. / Ji, Yanqing; Ying, Hao; Yen, John; Zhu, Shizhuo; Barth-Jones, Daniel C.; Miller, Richard E.; Massanari, R. Michael.

In: International Journal of Intelligent Systems, Vol. 22, No. 8, 01.08.2007, p. 827-845.

Research output: Contribution to journalArticle

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