Article | Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016 | Artificial Neural Networks Application in Intraocular Lens Power Calculation Linköping University Electronic Press Conference Proceedings
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Title:
Artificial Neural Networks Application in Intraocular Lens Power Calculation
Author:
Martin Sramka: Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic Alzbeta Vlachynska: Faculty of Applied Informatics, Tomas Bata University in Zlin, Zlin, Czech Repubic
DOI:
10.3384/ecp1714225
Download:
Full text (pdf)
Year:
2018
Conference:
Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Issue:
142
Article no.:
004
Pages:
25-30
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2018-12-19
ISBN:
978-91-7685-399-3
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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This article deals with intra-ocular lens (IOL) power calculations during the cataract surgery. At present, IOL power calculated by formulas is usually able to provide acceptable results for the majority of the patients. The problem appears when any of input parameters have the value which is not normal in population distribution. Then the patient post-operative refraction result can inconsiderable deviate from intended target. This work describes approach how to preoperatively indicate which samples of a patient could be problematic in accurate IOL calculations by classi?cation of Arti?cial Neural Networks (ANN). Small and long eyes are used to test the ability of ANN to classify input samples which are taken from pre-operative measurements to several groups which represent probable post-operative result. In our experiment, ANN classi?es samples into two groups. The ?rst group is for data samples with a probable result in positive ranges of diopter and second group is for negative ranges. The accuracy of ANN, in this case, is 94.1 %.

Keywords: intra-ocular lens (IOL) power calculation, arti?cial neural networks (ANN), cataract surgery, refraction result

Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016

Author:
Martin Sramka, Alzbeta Vlachynska
Title:
Artificial Neural Networks Application in Intraocular Lens Power Calculation
DOI:
http://dx.doi.org/10.3384/ecp1714225
References:
No references available

Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016

Author:
Martin Sramka, Alzbeta Vlachynska
Title:
Artificial Neural Networks Application in Intraocular Lens Power Calculation
DOI:
https://doi.org10.3384/ecp1714225
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment


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Last updated: 2019-10-02