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An adaptive two-tier menu approach to support on-line entry of diagnoses

  • Sugath K. Mudali
  • James R. Warren
  • Susan E. Spenceley
Knowledge Acquisition and Learning
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1211)

Abstract

We demonstrate how a task model derived from data mining techniques could be used to anticipate diagnosis codes from patient complaints for improved data entry efficiency. The anticipated diagnoses are presented to the user in a two-tier fashion with the first tier presenting the most likely diagnoses based upon the complaints which the second tier refines. A success rate of 70% was obtained in anticipating patient diagnosis.

Category

knowledge acquisition & learning 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Sugath K. Mudali
    • 1
  • James R. Warren
    • 1
  • Susan E. Spenceley
    • 1
  1. 1.Advanced Computing Research Centre, School of Computer and Information ScienceUniversity of South AustraliaThe LevelsAustralia

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