Fig. 3
From: Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment
(A) T-distributed stochastic neighbor embedding (t-SNE) plot. This nonlinear dimension reduction technique is used to visualize high-latitude data. (B) Selected variables by subphenotype in CA and the differences in the standardized values of each variable by subphenotype. All continuous variables were transformed into z-scores (mean: 0, standard deviation: −1 to 1)
WBC, white blood cell count; MAP, mean arterial pressure