TbiExtractor: A framework for extracting traumatic brain injury common data elements from radiology reports.

ABSTRACT:

Background

The manual extraction of valuable data from electronic medical records is cumbersome, error-prone, and inconsistent. By automating extraction in conjunction with standardized terminology, the quality and consistency of data utilized for research and clinical purposes would be substantially improved. Here, we set out to develop and validate a framework to extract pertinent clinical conditions for traumatic brain injury (TBI) from computed tomography (CT) reports.

Methods

We developed tbiExtractor, which extends pyConTextNLP, a regular expression algorithm using negation detection and contextual features, to create a framework for extracting TBI common data elements from radiology reports. The algorithm inputs radiology reports and outputs a structured summary conta

SUBMITTER: Mahan M 

PROVIDER: S-EPMC7329124 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature