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https://doi.org/10.2498/cit.2001.02.03

The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set

Jan Piecha

Puni tekst: engleski, pdf (878 KB) str. 123-132 preuzimanja: 368* citiraj
APA 6th Edition
Piecha, J. (2001). The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set. Journal of computing and information technology, 9 (2), 123-132. https://doi.org/10.2498/cit.2001.02.03
MLA 8th Edition
Piecha, Jan. "The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set." Journal of computing and information technology, vol. 9, br. 2, 2001, str. 123-132. https://doi.org/10.2498/cit.2001.02.03. Citirano 05.04.2020.
Chicago 17th Edition
Piecha, Jan. "The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set." Journal of computing and information technology 9, br. 2 (2001): 123-132. https://doi.org/10.2498/cit.2001.02.03
Harvard
Piecha, J. (2001). 'The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set', Journal of computing and information technology, 9(2), str. 123-132. https://doi.org/10.2498/cit.2001.02.03
Vancouver
Piecha J. The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set. Journal of computing and information technology [Internet]. 2001 [pristupljeno 05.04.2020.];9(2):123-132. https://doi.org/10.2498/cit.2001.02.03
IEEE
J. Piecha, "The Neural Network Selection for a Medical Diagnostic System using an Artificial Data Set", Journal of computing and information technology, vol.9, br. 2, str. 123-132, 2001. [Online]. https://doi.org/10.2498/cit.2001.02.03

Sažetak
The paper describes experiments with a neural network selection that works as a conclusion-making unit of walk-abnormalities diagnosis. The diagnostic interfaces described in this paper provide the user with various tools for the disease analysis. They are having a pressure and load distribution on the foot, while taking into account the individual characteristics of the patient standing and walking (1), (2), (3). Various visualisation options give the user many aims in putting the diagnosis anyhow, in order to simplify the diagnostic process several methods for the data record filtering have been implemented. The discussed methods of the neural network selection and training show how to avoid difficulties with limited number of available data records, needed for the conclusion algorithms effectiveness improvement.

Hrčak ID: 44813

URI
https://hrcak.srce.hr/44813

Posjeta: 516 *