Figure 6.

Risk factors and clinical prognosis analysis for critical illness

(A) ROC for a binary classification of progression to critical illness in the internal testing dataset.

(B) Diagnostic accuracy for critical illness progression prediction represented by a confusion matrix.

(C and D) Predictive features for critical illness progression through Shapley Additive exPlanation (SHAP) value analysis.

(E) Correlative analysis of predictive features influencing progression to critical illness.

(F) When patients were stratified into high-risk and low-risk groups, the Kaplan-Meier curves demonstrated a significant difference in survival probabilities.