@article{Ninos2021,

title = {Uncertainty Quantification, Implementations in Human Hemodynamics Flows},

author = {G. Ninos and V. Bartzis and N. Merlemis and I. Sarris},

url = {https://pubmed.ncbi.nlm.nih.gov/33721602/},

doi = {https://doi.org/10.1016/j.cmpb.2021.106021},

year  = {2021},

date = {2021-03-02},

journal = {Computer Methods and Programs in Biomedicine},

abstract = {Background and objective: Human hemodynamic modeling is usually influenced by uncertainties occurring from a considerable unavailability of information linked to the boundary conditions and the physical properties used in the numerical models. Calculating the effect of these uncertainties on the numerical findings along the cardiovascular system is a demanding process due to the complexity of the morphology of the body and the area dynamics. To cope with all these difficulties, Uncertainty Quantification (UQ) methods seem to be an ideal tool.

Results: This study focuses on analyzing and summarizing some of the recent research efforts and directions of implementing UQ in human hemodynamic flows by analyzing 139 research papers. Initially, the suitability of applying this approach is analyzed and demonstrated. Then, an overview of the most significant research work in various fields of biomedical hemodynamic engineering is presented. Finally, it is attempted to identify any possible forthcoming directions for research and methodological progress of UQ in biomedical sciences.

Conclusion: This review concludes that by finding the best statistical methods and parameters to represent the propagated uncertainties, while achieving a good interpretation of the interaction between input-output, is crucial for implementing UQ in biomedical sciences.

Keywords: Biomedical sciences; Computational fluid dynamics; Hemodynamic flows; Polynomial chaos; Uncertainty quantification. },

keywords = {biomedical sciences, computational fluid dynamics, hemodynamic flows, polynomial chaos, uncertainty quantification},

pubstate = {published},

tppubtype = {article}

}