Mining Diagnostic Rules with Taxonomy from Medical Databases

  • Shusaku Tsumoto
Conference paper

DOI: 10.1007/978-3-540-39592-8_7

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2871)
Cite this paper as:
Tsumoto S. (2003) Mining Diagnostic Rules with Taxonomy from Medical Databases. In: Zhong N., Raś Z.W., Tsumoto S., Suzuki E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science, vol 2871. Springer, Berlin, Heidelberg

Abstract

Experts’ reasoning in which selects the final diagnosis from many candidates consists of hierarchical differential diagnosis. In other words, candidates gives a sophisticated hiearchical taxonomy, usally described as a tree.

In this paper, the characteristics of experts’ rules are closely examined from the viewpoint of hiearchical decision steps and and a new approach to rule mining with extraction of diagnostic taxonomy from medical datasets is introduced. The key elements of this approach are calculation of the characterization set of each decision attribute (a given class) and the similarities between characterization sets. From the relations between similarities, tree-based taxonomy is obtained, which includes enough information for diagnostic rules.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Shusaku Tsumoto
    • 1
  1. 1.Department of Medical InformaticsShimane Medical University, School of MedicineIzumo City, ShimaneJapan

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