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Heterogeneous knowledge representation using a finite automaton and first order logic: a case study in electromyography

Abstract : In a certain number of situations, human cognitive functioning is difficult to represent with classical artificial intelligence structures. Such a difficulty arises in the polyneuropathy diagnosis which is based on the spatial distribution, along the nerve fibres, of lesions, together with the synthesis of several partial diagnoses. Faced with this problem while building up an expert system (NEUROP), we developed a heterogeneous knowledge representation associating a finite automaton with first order logic. A number of knowledge representation problems raised by the electromyography test features are examined in this study and the expert system architecture allowing such a knowledge modeling are laid out.
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https://hal.archives-ouvertes.fr/hal-00371948
Contributeur : Vincent Rialle <>
Soumis le : lundi 30 mars 2009 - 18:31:17
Dernière modification le : jeudi 21 mars 2019 - 14:56:08
Document(s) archivé(s) le : jeudi 10 juin 2010 - 19:17:32

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  • HAL Id : hal-00371948, version 1
  • ARXIV : 0903.5289

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Vincent Rialle, Annick Vila, Yves Besnard. Heterogeneous knowledge representation using a finite automaton and first order logic: a case study in electromyography. Artificial Intelligence in Medicine, Elsevier, 1991, 3 (2), pp.65-74. ⟨hal-00371948⟩

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