APPLICATION OF NEURAL NETWORKS IN PREDICTION OF TENSILE STRENGTH OF ABSORBABLE SUTURES

Robert  KARPIŃSKI; Jakub  GAJEWSKI; Jakub  SZABELSKI; Dalibor BARTA

doi:10.23743/acs-2017-31

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Published: Dec 30, 2017

DOI: https://doi.org/10.23743/acs-2017-31

DOI

https://doi.org/10.23743/acs-2017-31

Authors

Robert KARPIŃSKI

r.karpinski@pollub.pl

Lublin University of Technology, Faculty of Mechanical Engineering, Department of Machine Design and Mechatronics, Nadbystrzycka 36, 20-618 Lublin

Jakub GAJEWSKI

j.gajewski@pollub.pl

Lublin University of Technology, Faculty of Mechanical Engineering, Department of Machine Design and Mechatronics, Nadbystrzycka 36, 20-618 Lublin,

Jakub SZABELSKI

j.szabelski@pollub.pl

Lublin University of Technology, Faculty of Mechanical Engineering, Institute of Technological Systems of Information, Nadbystrzycka 36, 20-618 Lublin

Dalibor BARTA

dalibor.barta@fstroj.uniza.sk

University of Zilina, Faculty of Mechanical Engineering, Univerzitna 1, 01026 Zilina

Abstract

The paper presents results of research on neural network application in forecasting the tensile strength of two types of sutures. The preliminary research was conducted in order to establish the accuracy of the proposed method and will be used for formulating further research areas. The neural network enabled evaluation of suture material degradation after 3-to-6-days’ exposure to Ringer’s solution. The encountered problems regarding inaccuracies show that developing a single model for sutures may be difficult or impossible. Therefore future research should be conducted for a single type of sutures only and require applying additional parameters for the neural network.

Keywords:

neural network application, forecasting, sutures tensile

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KARPIŃSKI, R. ., GAJEWSKI, J. ., SZABELSKI, J. ., & BARTA, D. (2017). APPLICATION OF NEURAL NETWORKS IN PREDICTION OF TENSILE STRENGTH OF ABSORBABLE SUTURES. Applied Computer Science, 13(4), 76–86. https://doi.org/10.23743/acs-2017-31

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