Optimization of primary screw stability in Trabecular bone using neural network-based models
Multiple linear regression models were found to be insufficient for generating optimized screw configurations, and more complex surrogate models, such as NN, are needed. It could be concluded that different trabecular bone morphologies can benefit from distinct optimal screw designs. The insights gained from this study could have implications for the development of patient-specific orthopaedic treatments.
Authors
- Benedikt Helgason (ORCID: https://orcid.org/0000-0001-8324-2651)
- Cecilia Persson (ORCID: https://orcid.org/0000-0001-6663-6536)
- Yijun Zhou (ORCID: https://orcid.org/0000-0003-3961-0466)
- Stephen J. Ferguson (ORCID: https://orcid.org/0000-0003-0650-5889)
Institutions
- Uppsala University (SE)
- ETH Zurich (CH)
- Institute for Biomedical Engineering (CH)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1016/j.cmpb.2025.108720
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Horizon 2020
- H2020 Marie Skłodowska-Curie Actions