Machine Learning Model of Emergency Department Use for Patients Undergoing Treatment for Head and Neck Cancer Using Comprehensive Multifactor Electronic Health Records.

Our approach combining bootstrapped statistical profiling and ML importance analysis supported integration of clinician input to identify a distilled set of phenotypical characteristics for developing ML models predicting which patients undergoing head and neck cancer radiation therapy were at risk for ED visits.