Symbolical Reasoning about Numerical Data: A Hybrid Approach

  • Authors:
  • Christoph S. Herrmann

  • Affiliations:
  • Th Darmstadt, FB Informatik, FG Intellektik, Alexanderstr. 10, 64283 Darmstadt, Germany. E-mail: herrmann@informatik.th-darmstadt.de

  • Venue:
  • Applied Intelligence
  • Year:
  • 1997

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Abstract

By combining methods from artificial intelligence and signalanalysis, we have developed a hybrid system for medical diagnosis. The coreof the system is a fuzzy expert system with a dual source knowledge base.Two sets of rules are acquired, automatically from given examples andindirectly formulated by the physician. A fuzzy neural network serves tolearn from sample data and allows to extract fuzzy rules for the knowledgebase. A complex signal transformation preprocesses the digital data a priorito the symbolic representation. Results demonstrate the high accuracy of thesystem in the field of diagnosing electroencephalograms where it outperformsthe visual diagnosis by a human expert for some phenomena.