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Journal of Medical Systems

, Volume 21, Issue 6, pp 429–444 | Cite as

Induction of Decision Trees and Bayesian Classification Applied to Diagnosis of Sport Injuries

  • Igor Zelič
  • Igor Kononenko
  • Nada Lavrač
  • Vanja Vuga
Article

Abstract

Machine learning techniques can be used to extract knowledge from data stored in medical databases. In our application, various machine learning algorithms were used to extract diagnostic knowledge which may be used to support the diagnosis of sport injuries. The applied methods include variants of the Assistant algorithm for top-down induction of decision trees, and variants of the Bayesian classifier. The available dataset was insufficient for reliable diagnosis of all sport injuries considered by the system. Consequently, expert-defined diagnostic rules were added and used as pre-classifiers or as generators of additional training instances for diagnoses for which only few training examples were available. Experimental results show that the classification accuracy and the explanation capability of the naive Bayesian classifier with the fuzzy discretization of numerical attributes were superior to other methods and estimated as the most appropriate for practical use.

machine learning Bayesian classification 

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Copyright information

© Plenum Publishing Corporation 1997

Authors and Affiliations

  • Igor Zelič
    • 1
  • Igor Kononenko
    • 2
  • Nada Lavrač
    • 3
  • Vanja Vuga
    • 4
  1. 1.INFONETKranjSlovenia
  2. 2.Faculty of Computer and Information ScienceLjubljanaSlovenia
  3. 3.J. Stefan InstituteLjubljanaSlovenia
  4. 4.University Medical Centre for Sport MedicineLjubljanaSlovenia

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