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Application of an adaptive hybrid neural network to medical diagnosis. (English) Zbl 1002.68803

Sinčák, Peter (ed.) et al., The state of the art in computational intelligence. Proceedings of the European symposium on computational intelligence, Košice, Slovak Republic, August 30-September 1, 2000. With Forewords by Lotfi A. Zadeh, David E. Goldberg and Kunihiko Fukushima. Heidelberg: Physica-Verlag. Advances in Soft Computing. 329-336 (2000).
Summary: We have previously devised a hybrid neural network, based on the synergism of the Fuzzy ARTMAP and Probabilistic Neural Networks, for on-line pattern classification and probability estimation tasks. In this paper, we investigate the applicability of the hybrid network to medical diagnosis problems. In particular, the network was employed to predict and classify Myocardial Infarction patients into two categories (positive and negative cases) using a database of real records collected from a hospital. A number of experiments was conducted to evaluate the effects of several network parameters on its performance. The results are discussed and compared with those from the Fuzzy ARTMAP network.
For the entire collection see [Zbl 0978.00038].

MSC:

68U99 Computing methodologies and applications
68T05 Learning and adaptive systems in artificial intelligence
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