Dataset Information

Deep learning detects and visualizes bleeding events in electronic health records.

ABSTRACT:

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.

Patients/methods

Three hundred electronic health records with International Classification of Diseases, Tenth Revision diagnosis codes for bleeding or leukemia were extracted. Each sentence in the electronic health record was annotated as positive or negative for bleeding. The annotated sentences were used to develop a deep learning model that detects bleeding at sentence and note level.