Fig. 5From: Splicing factor-mediated regulation patterns reveals biological characteristics and aid in predicting prognosis in acute myeloid leukemiaConstruction of risk scoring model. A Identification of DEGs with different splicing regulation patterns. B Identification of DEGs significantly associated with prognosis by Cox regression analysis. C Calculate log(λ) of the minimum tenfold cross-validation error point and determine the corresponding model gene. D Determine the coefficients of model genes. E Survival analysis between high-risk score and low-risk score subgroups. F Time-dependent ROC curve analysis of risk score. G Univariate Cox regression analysis of clinicopathological factors and risk score. H Multivariate Cox regression analysis of clinicopathological factors and risk score. I Alluvial diagram showing the changes of splicing regulation patterns, risk score groups, survival status groups. J Differences in risk scores among different splicing regulation patterns and survival status groupsBack to article page