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Representing CARE rules in a decision-theoretic formalism

M M Wagner1, J M Overhage, E Rodriguez

  • 1Center for Biomedical Informatics, University of Pittsburgh, USA.

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1996
PubMed
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This study enhances reminder systems using a decision-theoretic model. The improved model explicitly represents uncertainty, costs, and benefits for better performance.

Area of Science:

  • Artificial Intelligence
  • Decision Theory
  • Computer Science

Background:

  • Reminder systems can be improved with novel representations.
  • Current systems may lack explicit reasoning about reminder probabilities and utilities.

Purpose of the Study:

  • To extend a decision-theoretic model for reminder systems.
  • To explicitly represent uncertainty, costs, and benefits of sending reminders.
  • To remove the assumption of reminder independence.

Main Methods:

  • Extended a previously described decision-theoretic model.
  • Incorporated explicit representation of true/false alarm probabilities and relative utilities.
  • Analyzed CARE rules to demonstrate representational capability.

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Main Results:

  • The enhanced model explicitly represents uncertainty, costs, and benefits.
  • The model can represent previously defined CARE rules.
  • The approach removes the assumption of reminder independence.

Conclusions:

  • Decision-theoretic representations offer a promising approach for enhancing reminder system performance.
  • The extended model provides a more comprehensive framework for reasoning about reminders.