https://oldena.lpnu.ua/handle/ntb/52542| Title: | Selection the “Saturated” Block from Interval System of Linear Algebraic Equations for Recurrent Laryngeal Nerve Identification |
| Authors: | Dyvak, Mykola Oliynyk, Iryna Pukas, Andriy Melnyk, Andriy |
| Affiliation: | Ternopil National Economic University |
| Bibliographic description (Ukraine): | Selection the “Saturated” Block from Interval System of Linear Algebraic Equations for Recurrent Laryngeal Nerve Identification / Mykola Dyvak, Iryna Oliynyk, Andriy Pukas, Andriy Melnyk // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 444–448. — (Hybrid Systems of Computational Intelligence). |
| Bibliographic description (International): | Selection the “Saturated” Block from Interval System of Linear Algebraic Equations for Recurrent Laryngeal Nerve Identification / Mykola Dyvak, Iryna Oliynyk, Andriy Pukas, Andriy Melnyk // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 444–448. — (Hybrid Systems of Computational Intelligence). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | neck surgery recurrent laryngeal nerve design of experiment interval analysis interval model |
| Number of pages: | 5 |
| Page range: | 444-448 |
| Start page: | 444 |
| End page: | 448 |
| Abstract: | The task of design a “saturated” experiment for measuring the characteristics of tissues in surgical wound in order to identify the recurrent laryngeal nerve (RLN) during operation on the neck organs considered in this paper. In this task, the method of selection a “saturated” block from an interval system of linear algebraic equations (ISLAE) is used, which allows to reduce the duration of surgical operation by decreasing the number of points for stimulation the surgical wound tissues to detect the RLN location and reduce the risk of its damage. |
| URI: | https://ena.lpnu.ua/handle/ntb/52542 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| References (Ukraine): | [1] M. C. D. Poveda, G. Dionigi, A. Sitges-Serra, M. Barczynski, P. Angelos, H. Dralle, E. Phelan and G. Randolph, “Intraoperative Monitoring of the Recurrent Laryngeal Nerve during Thyroidectomy: A Standardized Approach (Part 2),” World Journal of Endocrine Surgery, vol. 4, no. 1, pp. 33-40, 2012. [2] V. K. Dhillon, and R. P. Tufano, “The pros and cons to real-time nerve monitoring during recurrent laryngeal nerve dissection: an analysis of the data from a series of thyroidectomy patients,” Gland Surgery, vol. 6, no. 6, pp. 608-610, 2017. [3] H. Y. Kim, X. Liu, C. W. Wu, Y. J. Chai, and G. Dionigi, “Future Directions of Neural Monitoring in Thyroid Surgery,” Journal of Endocrine Surgery, vol. 17, no. 3, pp. 96-103, 2017. [4] W. E. Davis, J. L. Rea, and J. Templer, “Recurrent laryngeal nerve localization using a microlaryngeal electrode,” Otolaryngology – Head and Neck Surgery, vol, 87, no. 3, pp. 330-333, 1979. [5] M. Dyvak, O. Kozak, and A. Pukas, “Interval model for identification of laryngeal nerves,” Przegląd Elektrotechniczny, vol. 86, no. 1, pp. 139-140, 2010. [6] N. Porplytsya, and M. Dyvak, “Interval difference operator for the task of identification recurrent laryngeal nerve,” 16th International Conference On Computational Problems of Electrical Engineering (CPEE), pp. 156-158, 2015. [7] M. Dyvak, and I. Oliynyk, “Estimation Method for a Set of Solutions to Interval System of Linear Algebraic Equations with Optimized “Saturated Block” Selection Procedure,” Computational Problems of Electrical Engineering, Lviv, vol. 7, no. 1, pp. 17-24, 2017. [8] C. F. J. Wu, and M. S. Hamada, Experiments: Planning, Analysis and Optimization. Wiley, 2009. [9] M. Dyvak, N. Kasatkina, A. Pukas, and N. Padletska, “Spectral analysis the information signal in the task of identification the recurrent laryngeal nerve in thyroid surgery,” Przegląd Elektrotechniczny, vol. 89, no. 6, рр. 275- 277, 2013. [10] Götz Alefeld, and Jürgen Herzberger, Introduction to interval computations (Computer Science and Applied Mathematics). Academic Press, Inc. [Harcourt Brace Jovanovich, Publishers], New York, 1983. [11] S. P. Shary, “Algebraic Approach to the Interval Linear Static Identification, Tolerance, and Control Problems, or One More Application of Kaucher Arithmetic,” Reliable Computing, vol. 2(1), pp. 3–33, 1996. [12] E. Walter, and L. Pronzato, Identification of parametric model from experimental data. London, Berlin, Heidelberg, New York, Paris, Tokyo: Springer, 1997. [13] A. Kurzhanski and I. Valyi, Ellipsoidal Calculus for Estimation and Control. Birkhauser, Berlin, 1997. |
| References (International): | [1] M. C. D. Poveda, G. Dionigi, A. Sitges-Serra, M. Barczynski, P. Angelos, H. Dralle, E. Phelan and G. Randolph, "Intraoperative Monitoring of the Recurrent Laryngeal Nerve during Thyroidectomy: A Standardized Approach (Part 2)," World Journal of Endocrine Surgery, vol. 4, no. 1, pp. 33-40, 2012. [2] V. K. Dhillon, and R. P. Tufano, "The pros and cons to real-time nerve monitoring during recurrent laryngeal nerve dissection: an analysis of the data from a series of thyroidectomy patients," Gland Surgery, vol. 6, no. 6, pp. 608-610, 2017. [3] H. Y. Kim, X. Liu, C. W. Wu, Y. J. Chai, and G. Dionigi, "Future Directions of Neural Monitoring in Thyroid Surgery," Journal of Endocrine Surgery, vol. 17, no. 3, pp. 96-103, 2017. [4] W. E. Davis, J. L. Rea, and J. Templer, "Recurrent laryngeal nerve localization using a microlaryngeal electrode," Otolaryngology – Head and Neck Surgery, vol, 87, no. 3, pp. 330-333, 1979. [5] M. Dyvak, O. Kozak, and A. Pukas, "Interval model for identification of laryngeal nerves," Przegląd Elektrotechniczny, vol. 86, no. 1, pp. 139-140, 2010. [6] N. Porplytsya, and M. Dyvak, "Interval difference operator for the task of identification recurrent laryngeal nerve," 16th International Conference On Computational Problems of Electrical Engineering (CPEE), pp. 156-158, 2015. [7] M. Dyvak, and I. Oliynyk, "Estimation Method for a Set of Solutions to Interval System of Linear Algebraic Equations with Optimized "Saturated Block" Selection Procedure," Computational Problems of Electrical Engineering, Lviv, vol. 7, no. 1, pp. 17-24, 2017. [8] C. F. J. Wu, and M. S. Hamada, Experiments: Planning, Analysis and Optimization. Wiley, 2009. [9] M. Dyvak, N. Kasatkina, A. Pukas, and N. Padletska, "Spectral analysis the information signal in the task of identification the recurrent laryngeal nerve in thyroid surgery," Przegląd Elektrotechniczny, vol. 89, no. 6, rr. 275- 277, 2013. [10] Götz Alefeld, and Jürgen Herzberger, Introduction to interval computations (Computer Science and Applied Mathematics). Academic Press, Inc. [Harcourt Brace Jovanovich, Publishers], New York, 1983. [11] S. P. Shary, "Algebraic Approach to the Interval Linear Static Identification, Tolerance, and Control Problems, or One More Application of Kaucher Arithmetic," Reliable Computing, vol. 2(1), pp. 3–33, 1996. [12] E. Walter, and L. Pronzato, Identification of parametric model from experimental data. London, Berlin, Heidelberg, New York, Paris, Tokyo: Springer, 1997. [13] A. Kurzhanski and I. Valyi, Ellipsoidal Calculus for Estimation and Control. Birkhauser, Berlin, 1997. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Dyvak_M-Selection_the_Saturated_444-448.pdf | 312.87 kB | Adobe PDF | View/Open | |
| 2018_Dyvak_M-Selection_the_Saturated_444-448__COVER.png | 527.63 kB | image/png | View/Open |
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