A natural language processing system to extract and code concepts relating to congestive heart failure from chest radiology reports.
Year: 2006
Type: article
Abstract: We have developed a natural language processing system for extracting and coding clinical data from free text reports. The system is designed to be easily modified and adapted to a variety of free text clinical reports such as admission notes, radiology and pathology reports, and discharge summaries. This report presents the results of this system to extract and code clinical concepts related to congestive heart failure from 39,000 chest radiology reports. The system detects the presence or absence of six concepts: congestive heart failure, Kerley B lines, cardiomegaly, prominent pulmonary vasculature, pulmonary edema, and pleural effusion. We compared it's output to a gold standard which consisted of specially trained human coders as well as an experienced physician. Results indicate that the system had high specificity, recall and precision for each of the concepts it is designed to detect.
Source: Europe PMC (PubMed Central)
Authors: Jeff Friedlin, Clement J McDonald
Institutions: Regenstrief Institute, Indiana University School of Medicine
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W280670494