Figure 6.(A) Regions of interest were manually segmented. (B) A total of 396 features were extracted. (C) Features were selected using LASSO method. (D) Rad-score was calculated. (E) Predicting model was developed using support vector machine.
Figure 6 — Predicting intraventricular hemorrhage growth with a machine learning-based, radiomics-clinical model | Aging
