Interactive NLP in Clinical Care: Identifying Incidental Findings in Radiology Reports.

ABSTRACT:

Background

Despite advances in natural language processing (NLP), extracting information from clinical text is expensive. Interactive tools that are capable of easing the construction, review, and revision of NLP models can reduce this cost and improve the utility of clinical reports for clinical and secondary use.

Objectives

We present the design and implementation of an interactive NLP tool for identifying incidental findings in radiology reports, along with a user study evaluating the performance and usability of the tool.

Methods

Expert reviewers provided gold standard annotations for 130 patient encounters (694 reports) at sentence, section, and report levels. We performed a user study with 15 physicians to evaluate the accuracy and usability of our tool. Partici

SUBMITTER: Trivedi G 

PROVIDER: S-EPMC6727024 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature