Fig. 4 | Scientific Reports

Fig. 4

From: Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture

Fig. 4

Clustering of morphological (a) and hemodynamic (b) parameters to avoid multicollinearity in the regression analysis. Highly correlated variables were grouped into clusters, and for each cluster, the variable with the smallest and significant p-value in the univariate regression was selected as the representative. The clustering was performed based on the squared Pearson correlation coefficient (r2), using a cut-off of r2 > 0.25.

Back to article page