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Feature selection using Lasso regression. (A) Lasso coefficient profiles of the clinical features; (B) identification of the optimal penalization coefficient lambda (λ) using 10-fold cross-validation and the minimum plus 1 standard error criterion; (C) histogram shows that the presence of features selected by Lasso regression is more common in patients who ruptured than those who didn’t.
