Machine Learning Can Reduce Unnecessary Hospitalizations for Cancer Patients

Alexander Fuglkjær from Aalborg University presented promising results at ASH from a machine learning model designed to risk-stratify infection-related hospitalizations in cancer patients. The model identifies patients who can safely be sent home without risk of complications and shows potential for broader application across multiple cancer types.