Konstantinos Tzirakis

4. Discussion This work is among the few that have utilized advanced, outlier-robust statistical models to analyze blood flow simulations [,]. The results presented in the previous section demonstrate that associations between response variables that summarize hemodynamics with a graft’s main characteristics, namely its limb angle and diameter, can be captured with second-order predictive specifications, which include interaction effects.

Abstract Glioblastoma is the most aggressive and infiltrative glioma, classified as Grade IV, with the poorest survival rate among patients. Accurate and rigorously tested mechanistic in silico modeling offers great value to understand and quantify the progression of primary brain tumors. This paper presents a continuum-based finite element framework that is built on high performance computing, open-source libraries to simulate glioblastoma progression.

4. Discussion The statistical outcomes presented above possess a notable characteristic: robustness of the derived partitions, which are insensitive to the chosen clustering variant. This is rarely observed in practice and adds credibility to the model-groups depicted in Figure 7. Is there an agreement between the initial partitions of rheological specifications and the statistical estimates, which are based on simulated data from each model?