An interesting XGboost-based ML model with high AUC (0.92) for predicting sepsis in children (<19 years old) who had BM transplantation is reported in [22], wherein the model required 23 features, including vital signs, complete blood count (CBC), coagulation function, serum CRP (C-reactive protein), electrolytes (ca, Na, K), liver function indicators, and infection index. Here, CRP is linked to infection.