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Medical knowledge modeling in a symbolic-connectionist perspective

Vincent Rialle 1 M. Ohayon 2 Bernard Amy 3, 4 Pierre Bessiere 3, 4
1 TIMB
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525
Abstract : In this study, we show the specific and complementary attributes of Artificial Intelligence (AI) and of Connectionism (C). AI seems to be more adapted to modeling upper levels of data and knowledge processing performed by the brain, whereas C is more generally linked to sensory perception, reflexes or pattern recognition processes. A certain number of medical diagnosis aiding systems, combining these two paradigms, document the thesis that hybrid symbolic-connectionist architectures offer a very promising opening for the realization of complex, high level decision making systems in the years to come.
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Communication dans un congrès
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https://hal.archives-ouvertes.fr/hal-00089358
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Soumis le : dimanche 17 septembre 2006 - 07:00:01
Dernière modification le : jeudi 21 mars 2019 - 14:56:10
Document(s) archivé(s) le : lundi 5 avril 2010 - 22:41:17

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  • HAL Id : hal-00089358, version 1

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Vincent Rialle, M. Ohayon, Bernard Amy, Pierre Bessiere. Medical knowledge modeling in a symbolic-connectionist perspective. sdf, 1991, France. pp.Vol. 13 - N°3. ⟨hal-00089358⟩

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