The paper presents software units developed for visualisation and the automatic conclusion within feet abnormalities. These diagnostic interfaces provide the user with various tools for the disease analysis. They are having a pressure and load distribution on the feet, while taking into account the individual characteristics of the patient standing and walking [1],[2],[3]. A big number of options gives the user many aims in putting the diagnosis. The conclusion making system design methodology, described in this paper, shows how to avoid difficulties with a neural network structure and training methods selection, especially when limited number of data records is available. The experiments with the neural networks proved assumption that an artificial data record can be used for the network selection and for the neural network training. The artificial records are examined by filtering tools that have been developed as well.
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