Intelligent classifier based on radial basis function network for the task of identification the recurrent laryngeal nerve in a surgical wound

• Autorzy: Savka N. , Dyvak M. , Pukas A. , Nemish V.
• Języki publikacji: EN

Abstrakty

EN

The application of radial basis function networks (RBFN) for identification the recurrent laryngeal nerve (RLN) in a surgical wound was proved in this paper. The intelligent classifier based on artificial neural network with radial basis functions (RBF) was created. The task of identification the recurrent laryngeal nerve during thyroid surgery in the process of classification the information signals from different patients is considered.

Słowa kluczowe

EN

intelligent classifier; artificial neural networks; radial basis function networks; recurrent laryngeal nerve; identification

PL

separator inteligentny; sztuczne sieci neuronowe; sieci o radialnych funkcjach bazowych; nerw krtaniowy wsteczny; identyfikacja

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2014
• Tom: Vol. 22, nr 2
• Strony: 55--64
• Opis fizyczny: Bibliogr. 9 poz.

Twórcy

autor

Savka N.

• Ternopil National Economic University, Department of Computer Science, Yunosti str. 9, Ternopil, Ukraine, 46020

autor

Dyvak M.

• Ternopil National Economic University, Department of Computer Science, Yunosti str. 9, Ternopil, Ukraine, 46020

autor

Pukas A.

• Ternopil National Economic University, Department of Computer Science, Yunosti str. 9, Ternopil, Ukraine, 46020

autor

Nemish V.

• Ternopil National Economic University, Department of Computer Science, Yunosti str. 9, Ternopil, Ukraine, 46020

Bibliografia

• [1] Dyvak, M. P., Tasks of Mathematical Modeling the Static Systems with Interval Data, Economic thought, 2011.
• [2] Dyvak, M., Shidlovskiy, V. O., and Kozak, O. L., Patent of Ukraine for useful model # 51174. The Menner of Identification the Laryngeal Nerve from Other Tissue in Surgical Wound During Thyroid Surgery, Bull. “Industrial Property”, , No. 13, 2010, (in Ukraine).
• [3] Dyvak, M., Kasatkina, N., Pukas, A., and Padletska, N., Spectral Analysis the Information Signal in the Task of Identification the Recurrent Laryngeal Nerve in Thyroid Surgery, Przeglad Elektrotechniczny, ISSN 0033-2097, Vol. 89, No. 6, 2013, pp. 275–277.
• [4] Tymoshchuk, P. V. and Brenych, Y. V., Neural Methods for Solving the Classification Task, Scientific Bulletin of National Forestry University, Vol. 22.13, 2012, pp. 343–349, (in Ukraine).
• [5] Kala, R., Vazirani, H., Khanwalkar, N., and Bhattacharya, M., Evolutionary Radial Basis Function Network for Classificatory Problems, International Journal of Computer Science and Applications, Vol. 7, No. 4, 2010, pp. 34–49.
• [6] Hamad, A., Yu, D., Gomm, J. B., and Sangha, M. S., Radial basis function neural network in fault detection of automotive engines, International Journal of Engineering, Science and Technology, Vol. 2, No. 10, 2010, pp. 1–8.
• [7] Savka, N. Y., Spilchuk, V. M., and Spivak, I. Y., Problems of Identification the Radial Basis Function Networks and PossibleWays of Their Solving, Inductive modeling of complex systems, Vol. 2, 2010, pp. 181–193, (in Ukraine).
• [8] Shidlovskiy, V. O., Dyvak, M. P., Shidlovskiy, O. V., Kozak, O. L., and Roznovskyy, Y. R., Patent of Ukraine for useful model No. 66648. A Device for Identification the Laryngeal Nerve, Bull. “Industrial Property”, , No. 1, 2012, (in Ukraine).
• [9] Dyvak, M., Padletska, N., Pukas, A., and O., K., Identification the Recurrent Laryngeal Nerve by the Autocorrelation Function of Signal as Reaction on the Stimulation of Tissues in Surgical Wound. The Experience of Designing and Application of CAD Systems in Microelectronics. Proceedings of the XIIth International Conference CADSM’2013, Tech. rep., Publishing House of Lviv Polytechnic, 2013.