Automatic planning of treatment of infants with respiratory failure through rough set modeling

  • Authors:

  • Jan G. Bazan;Piotr Kruczek;Stanislawa Bazan-Socha;Andrzej Skowron;Jacek J. Pietrzyk

  • Affiliations:

  • Institute of Mathematics, University of Rzeszów, Rzeszów, Poland;Department of Pediatrics, Collegium Medicum, Jagiellonian University, Cracow, Poland;Department of Internal Medicine, Collegium Medicum, Jagiellonian University, Cracow, Poland;Institute of Mathematics, Warsaw University, Warsaw, Poland;Department of Pediatrics, Collegium Medicum, Jagiellonian University, Cracow, Poland

  • Venue:
  • RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
  • Year:
  • 2006

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Abstract

We discuss an application of rough set tools for modeling networks of classifiers induced from data and ontology of concepts delivered by experts. Such networks allow us to develop strategies for automated planning of a treatment of infants with respiratory illness. We report results of experiments with the networks of classifiers used in automated planning of the treatment of newborn infants with respiratory failure. The reported experiments were performed on medical data obtained from the Neonatal Intensive Care Unit in the Department of Pediatrics, Collegium Medicum, Jagiellonian University.