| DC Field | Value | Language |
|---|
| dc.contributor.author | Dyvak, Mykola | |
| dc.contributor.author | Oliynyk, Iryna | |
| dc.contributor.author | Pukas, Andriy | |
| dc.contributor.author | Melnyk, Andriy | |
| dc.coverage.temporal | 21-25 August 2018, Lviv | |
| dc.date.accessioned | 2020-06-19T12:06:02Z | - |
| dc.date.available | 2020-06-19T12:06:02Z | - |
| dc.date.created | 2018-02-28 | |
| dc.date.issued | 2018-02-28 | |
| dc.identifier.citation | 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). | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52542 | - |
| dc.description.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. | |
| dc.format.extent | 444-448 | |
| dc.language.iso | en | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 | |
| dc.subject | neck surgery | |
| dc.subject | recurrent laryngeal nerve | |
| dc.subject | design of experiment | |
| dc.subject | interval analysis | |
| dc.subject | interval model | |
| dc.title | Selection the “Saturated” Block from Interval System of Linear Algebraic Equations for Recurrent Laryngeal Nerve Identification | |
| dc.type | Conference Abstract | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2018 | |
| dc.contributor.affiliation | Ternopil National Economic University | |
| dc.format.pages | 5 | |
| dc.identifier.citationen | 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). | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [8] C. F. J. Wu, and M. S. Hamada, Experiments: Planning, Analysis and Optimization. Wiley, 2009. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [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. | |
| dc.relation.references | [12] E. Walter, and L. Pronzato, Identification of parametric model from experimental data. London, Berlin, Heidelberg, New York, Paris, Tokyo: Springer, 1997. | |
| dc.relation.references | [13] A. Kurzhanski and I. Valyi, Ellipsoidal Calculus for Estimation and Control. Birkhauser, Berlin, 1997. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [8] C. F. J. Wu, and M. S. Hamada, Experiments: Planning, Analysis and Optimization. Wiley, 2009. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [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. | |
| dc.relation.referencesen | [12] E. Walter, and L. Pronzato, Identification of parametric model from experimental data. London, Berlin, Heidelberg, New York, Paris, Tokyo: Springer, 1997. | |
| dc.relation.referencesen | [13] A. Kurzhanski and I. Valyi, Ellipsoidal Calculus for Estimation and Control. Birkhauser, Berlin, 1997. | |
| dc.citation.conference | IEEE second international conference "Data stream mining and processing" | |
| dc.citation.spage | 444 | |
| dc.citation.epage | 448 | |
| dc.coverage.placename | Львів | |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference
|
