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Uncertainty quantification implementations in human hemodynamic flows
G Ninos1, V Bartzis2, N Merlemis3
1Department of Biomedical Sciences, University of West Attica, 12243, Athens, Greece; Department of Mechanical Engineering, University of West Attica, 12244, Athens, Greece.
Computer Methods and Programs in Biomedicine
|March 15, 2021
Summary
Uncertainty Quantification (UQ) methods address data gaps in human hemodynamic modeling. This review highlights UQ
Area of Science:
- Biomedical Engineering
- Computational Fluid Dynamics
- Medical Physics
Background:
- Human hemodynamic modeling faces challenges due to missing boundary condition and material property data.
- Quantifying the impact of these uncertainties on cardiovascular system simulations is complex.
- Uncertainty Quantification (UQ) offers a robust framework to address these limitations.
Purpose of the Study:
- To review and synthesize recent research on UQ applications in human hemodynamic flows.
- To assess the suitability and demonstrate the application of UQ in this field.
- To identify future research directions and methodological advancements for UQ in biomedical sciences.
Main Methods:
- Systematic literature review of 139 research papers.
- Analysis of UQ implementation in various biomedical hemodynamic engineering domains.
- Synthesis of current research trends and identification of gaps.
Main Results:
- UQ is a suitable and effective approach for human hemodynamic modeling.
- Significant research efforts have been made in applying UQ across different biomedical fields.
- The review provides an overview of key studies and their findings.
Conclusions:
- Effective implementation of UQ in biomedical sciences requires optimal statistical methods for uncertainty representation.
- Interpreting the input-output interactions within UQ frameworks is crucial for reliable results.
- Further methodological progress in UQ is essential for advancing biomedical research.
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