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

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 (Poland)

Jakub GAJEWSKI


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

Jakub SZABELSKI


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

Dalibor BARTA


University of Zilina, Faculty of Mechanical Engineering, Univerzitna 1, 01026 Zilina (Slovakia)

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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Published
2017-12-30

Cited by

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

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 Poland

Authors

Jakub GAJEWSKI 

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

Authors

Jakub SZABELSKI 

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

Authors

Dalibor BARTA 

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

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