A Machine Learning Approach for Predicting In-Hospital Cardiac Arrest Using Single-Day Vital Signs, Laboratory Test Results, and International Classification of Disease-10 Block for Diagnosis

Incorporating laboratory test results or combining laboratory test results and ICD10BD with vital signs as predictor variables in the XGBoost model potentially enhances clinical decision-making and improves patient outcomes in hospital settings.