Prediction of intra-abdominal injury using natural language processing of electronic medical record data.

ABSTRACT:

Background

This study aimed to use natural language processing to predict the presence of intra-abdominal injury using unstructured data from electronic medical records.

Methods

This was a random-sample retrospective observational cohort study leveraging unstructured data from injured patients taken to one of 9 acute care hospitals in an integrated health system between 2015 and 2021. Patients with International Classification of Diseases External Cause of Morbidity codes were identified. History and physical, consult, progress, and radiology report text from the first 8 hours of care were abstracted. Annotator dyads independently annotated encounters' text files to establish ground truth regarding whether intra-abdominal injury occurred. Features were extracted from text us

SUBMITTER: Danna G 

PROVIDER: S-EPMC11330356 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature