Application of classification algorithms for hip implant surface topographies
Аутори
Vulović, AleksandraGeroski, Tijana
Filipović, Nenad
Остала ауторства
Morić, IvanaĐorđević, Valentina
Конференцијски прилог (Објављена верзија)
,
© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Метаподаци
Приказ свих података о документуАпстракт
Experimental studies have shown that lower shear stress values lead to better femoral
bone – hip implant connection. Numerical simulations have provided option to reduce
the number of experimental studies through analysis of different hip implant surface
topographies. However, this approach takes time as there are different model parameters
that should be considered in order to understand how they affect the obtained shear
stress values. The use of classification algorithms is an approach that could reduce the
time required for simulation by providing information about models with biggest potential.
Eleven model parameters related to model and surface topography were considered
in combination with four classification algorithms - Support Vector Machines (SVM), K
- Nearest Neighbor (KNN), Decision Tree (DT), and Random Forest (RF). The considered
parameters were: Number of half-cylinders lengthwise (>0); Number of half-cylinder rows
(≥0); Half cylinders added or removed from ...the surface (0 – removed; 1 - added); Distance
between half-cylinders lengthwise (≥0); Distance between half-cylinders widthwise
(≥0); Number of different radius values (1 or 2); Radius 1 value (>0); Radius 2 value (≥0);
Distance from the edge where loading is located (≥0); Distance from the other edge of the
model (≥0); Model includes trabecular bone (0 – not included; 1 - included). The aim was
to apply previously mentioned algorithms to obtain information if the maximum shear
stress value was above or below user-defined threshold. The obtained results show that
this approach can be useful to obtain preliminary information about models that should
be numerically analyzed.
Кључне речи:
classification / finite element analysis / hip implant / surface topographiesИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 41-41Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Финансирање / пројекти:
- This research is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 952603 - SGABU.
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200107 (Универзитет у Крагујевцу, Факултет инжењерских наука) (RS-MESTD-inst-2020-200107)
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Vulović, Aleksandra AU - Geroski, Tijana AU - Filipović, Nenad PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1979 AB - Experimental studies have shown that lower shear stress values lead to better femoral bone – hip implant connection. Numerical simulations have provided option to reduce the number of experimental studies through analysis of different hip implant surface topographies. However, this approach takes time as there are different model parameters that should be considered in order to understand how they affect the obtained shear stress values. The use of classification algorithms is an approach that could reduce the time required for simulation by providing information about models with biggest potential. Eleven model parameters related to model and surface topography were considered in combination with four classification algorithms - Support Vector Machines (SVM), K - Nearest Neighbor (KNN), Decision Tree (DT), and Random Forest (RF). The considered parameters were: Number of half-cylinders lengthwise (>0); Number of half-cylinder rows (≥0); Half cylinders added or removed from the surface (0 – removed; 1 - added); Distance between half-cylinders lengthwise (≥0); Distance between half-cylinders widthwise (≥0); Number of different radius values (1 or 2); Radius 1 value (>0); Radius 2 value (≥0); Distance from the edge where loading is located (≥0); Distance from the other edge of the model (≥0); Model includes trabecular bone (0 – not included; 1 - included). The aim was to apply previously mentioned algorithms to obtain information if the maximum shear stress value was above or below user-defined threshold. The obtained results show that this approach can be useful to obtain preliminary information about models that should be numerically analyzed. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Application of classification algorithms for hip implant surface topographies EP - 41 SP - 41 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_1979 ER -
@conference{ author = "Vulović, Aleksandra and Geroski, Tijana and Filipović, Nenad", year = "2023", abstract = "Experimental studies have shown that lower shear stress values lead to better femoral bone – hip implant connection. Numerical simulations have provided option to reduce the number of experimental studies through analysis of different hip implant surface topographies. However, this approach takes time as there are different model parameters that should be considered in order to understand how they affect the obtained shear stress values. The use of classification algorithms is an approach that could reduce the time required for simulation by providing information about models with biggest potential. Eleven model parameters related to model and surface topography were considered in combination with four classification algorithms - Support Vector Machines (SVM), K - Nearest Neighbor (KNN), Decision Tree (DT), and Random Forest (RF). The considered parameters were: Number of half-cylinders lengthwise (>0); Number of half-cylinder rows (≥0); Half cylinders added or removed from the surface (0 – removed; 1 - added); Distance between half-cylinders lengthwise (≥0); Distance between half-cylinders widthwise (≥0); Number of different radius values (1 or 2); Radius 1 value (>0); Radius 2 value (≥0); Distance from the edge where loading is located (≥0); Distance from the other edge of the model (≥0); Model includes trabecular bone (0 – not included; 1 - included). The aim was to apply previously mentioned algorithms to obtain information if the maximum shear stress value was above or below user-defined threshold. The obtained results show that this approach can be useful to obtain preliminary information about models that should be numerically analyzed.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Application of classification algorithms for hip implant surface topographies", pages = "41-41", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_1979" }
Vulović, A., Geroski, T.,& Filipović, N.. (2023). Application of classification algorithms for hip implant surface topographies. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 41-41. https://hdl.handle.net/21.15107/rcub_imagine_1979
Vulović A, Geroski T, Filipović N. Application of classification algorithms for hip implant surface topographies. in 4th Belgrade Bioinformatics Conference. 2023;4:41-41. https://hdl.handle.net/21.15107/rcub_imagine_1979 .
Vulović, Aleksandra, Geroski, Tijana, Filipović, Nenad, "Application of classification algorithms for hip implant surface topographies" in 4th Belgrade Bioinformatics Conference, 4 (2023):41-41, https://hdl.handle.net/21.15107/rcub_imagine_1979 .