Background: Bleeding is associated with a significantly increased morbidity and mortality. Bleeding events are often described in the unstructured text of electronic health records, which makes them difficult to identify by manual inspection.
Objectives: To develop a deep learning model that detects and visualizes bleeding events in electronic health records.