Symbolical Reasoning about Numerical Data: A Hybrid Approach |
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Authors: | Christoph S. Herrmann |
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Affiliation: | (1) Th Darmstadt, FB Informatik, FG Intellektik, Alexanderstr. 10, 64283 Darmstadt, Germany. E-mail |
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Abstract: | By combining methods from artificial intelligence and signal analysis, we have developed a hybrid system for medical diagnosis. The core of the system is a fuzzy expert system with a dual source knowledge base. Two sets of rules are acquired, automatically from given examples and indirectly formulated by the physician. A fuzzy neural network serves to learn from sample data and allows to extract fuzzy rules for the knowledge base. A complex signal transformation preprocesses the digital data a priori to the symbolic representation. Results demonstrate the high accuracy of the system in the field of diagnosing electroencephalograms where it outperforms the visual diagnosis by a human expert for some phenomena. |
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Keywords: | expert systems fuzzy logic hybrid systems medical diagnosis neural networks |
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