The dedicated decision support system in recognition of some uncertain disease entities

• Autorzy: Porwik P.
• Języki publikacji: EN

Abstrakty

EN

This work presents the principles of image recognition, where quality-based methods are applied. The neural networks and additional software have been proposed. This goal was achieved by using non-parametric recognition algorithms. In this paper the two-state hybrid classification method has been proposed, where artificial intelligence algorithm is included. In recognition process, the learning method, selection and optimization of diagnostic parameters have been introduced. The integrated part of the classifier structure is voting mechanism, which indicates incorrect states of the system – for example the unrecognized images. Effectiveness of the system has been shown by means of examples, where ambiguous data have been incorporated – it is very often a practice of medical diagnostics.

Słowa kluczowe

EN

image recognition; data classification; neural network; decision support systems

PL

rozpoznawanie obrazu; klasyfikacja danych; sieci neuronowe; systemy wspomagania decyzji

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2009
• Tom: Vol. 13
• Strony: 97--100
• Opis fizyczny: Bibliogr. 8 poz., rys.

Twórcy

autor

Porwik P.

• Institute of Informatics, University of Silesia, Będzińska 39, 41-200 Sosnowiec, Poland

Bibliografia

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• [3] KORBICZ J., i inni, Sztuczne sieci neuronowe. Podstawy i zastosowania. Akademicka Oficyna Wydawnicza, Warszawa 1994.
• [4] NIENIEWSKI, M., Probabilistic methods in pattern recognition and computer vision. Lecture Notes and Computer Vision and Artificial Intelligence, Ossolineum 1990, pp. 123-161.
• [5] PORWIK P.,ADAMCZEWSKI J., The object states classification method in diagnostics experiment. XXIV Ogólnopolskie Sympozjum DIAGNOSTYKA MASZYN. Politechnika Śląska, Zeszyt 1/ 1997, pp. 163-168.
• [6] SOBCZAK W., MALINA W., Metody selekcji i redukcji informacji. WNT, Warszawa 1985.
• [7] RUTKOWSKA D. i inni, Sieci neuronowe, algorytmy genetyczne i systemy rozmyte. PWN, Warszawa 1997.
• [8] TADEUSIEWICZ R., Sieci neuronowe. Akademicka Oficyna Wydawnicza, Warszawa 1993.