Question-answering system extracts information on injection drug use from clinical notes.

ABSTRACT:

Background

Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients' electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools.

Methods

To address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our f

SUBMITTER: Mahbub M 

PROVIDER: S-EPMC10991373 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature