Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies

Both XGB and LR with median imputation demonstrated robust performance in predicting admissions in the presence of missing data. However, deriving clinically useful models for rare outcomes, such as ICU use or PLOS, remains a challenge due to poor precision/recall and calibration performance. Further research is needed to improve the prediction of rare outcomes in this population.