دورية أكاديمية
Efficient sensitivity analysis for biomechanical models with correlated inputs
| العنوان: | Efficient sensitivity analysis for biomechanical models with correlated inputs |
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| المؤلفون: | Hilhorst, Pjotr L. J., Quicken, Sjeng, van de Vosse, Frans N., Huberts, Wouter |
| المصدر: | Hilhorst , P L J , Quicken , S , van de Vosse , F N & Huberts , W 2024 , ' Efficient sensitivity analysis for biomechanical models with correlated inputs ' , International Journal for Numerical Methods in Biomedical Engineering , vol. 40 , no. 2 , e3797 . https://doi.org/10.1002/cnm.3797Test |
| سنة النشر: | 2024 |
| المجموعة: | Maastricht University Research Publications |
| مصطلحات موضوعية: | correlated input, pulse wave propagation model, sensitivity analysis, surrogate modeling, PULSE-WAVE PROPAGATION, CARDIOVASCULAR MODELS, VALIDATION, INDEXES, INTERPOLATION, VESSELS, SUPPORT, DESIGN, FLOW |
| الوصف: | In most variance-based sensitivity analysis (SA) approaches applied to biomechanical models, statistical independence of the model input is assumed. However, often the model inputs are correlated. This might alter the interpretation of the SA results, which may severely impact the guidance provided during model development and personalization. Potential reasons for the infrequent usage of SA techniques that account for input correlation are the associated high computational costs, especially for models with many parameters, and the fact that the input correlation structure is often unknown. The aim of this study was to propose an efficient correlated global sensitivity analysis method by applying a surrogate model-based approach. Furthermore, this article demonstrates how correlated SA should be interpreted and how the applied method can guide the modeler during model development and personalization, even when the correlation structure is not entirely known beforehand. The proposed methodology was applied to a typical example of a pulse wave propagation model and resulted in accurate SA results that could be obtained at a theoretically 27,000x lower computational cost compared to the correlated SA approach without employing a surrogate model. Furthermore, our results demonstrate that input correlations can significantly affect SA results, which emphasizes the need to thoroughly investigate the effect of input correlations during model development. We conclude that our proposed surrogate-based SA approach allows modelers to efficiently perform correlated SA to complex biomechanical models and allows modelers to focus on input prioritization, input fixing and model reduction, or assessing the dependency structure between parameters.Surrogate model-based sensitivity analysis is a quick and efficient way to perform sensitivity analysis whilst taking into account correlations between input parameters. The efficiency of the sensitivity analysis allows to modeler to assess if investigating the correlation structure of ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | https://cris.maastrichtuniversity.nl/en/publications/96ec2680-ddfc-47be-91f2-cdf503b4c6cdTest |
| DOI: | 10.1002/cnm.3797 |
| الإتاحة: | https://doi.org/10.1002/cnm.3797Test https://cris.maastrichtuniversity.nl/en/publications/96ec2680-ddfc-47be-91f2-cdf503b4c6cdTest |
| حقوق: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.BAB864B5 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1002/cnm.3797 |
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