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An Evolutionary Computational Approach to Probabilistic Neural Network with Application to Hepatic Cancer Diagnosis
Dublin, Ireland June 23-June 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.2418th IEEE Symposium on Computer-Based ...
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Florin Gorunescu, University of Medicine and Pharmacy of Craiova
Marina Gorunescu, University of Craiova
Elia El-Darzi, University of Westminster
Smaranda Gorunescu, University of Craiova
The performance of a probabilistic neural network is strongly influenced by the smoothing parameter. This paper introduces an evolutionary approach based on genetic algorithm to optimise the search of the smoothing parameter in a modified probabilistic neural network. A Java implementation is introduced and the computational results showed the viability of this hybrid approach to determine the optimum diagnosis for hepatic diseases.
Citation:
Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Smaranda Gorunescu, "An Evolutionary Computational Approach to Probabilistic Neural Network with Application to Hepatic Cancer Diagnosis," cbms, pp.461-466, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005
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