Using a natural language processing system to extract and code family history data from admission reports.
Year: 2006
Type: article
Abstract: We developed a rule-based natural language processing (NLP) system for extracting and coding clinical data from free text reports. We studied the systems ability to accurately extract and code family history data from hospital admission notes. The system searches the family history for 12 diseases (and relative degree). It achieved a sensitivity of .96 and a PPV of .97 for disease extraction, and .96 and .93 respectively for relative categorization.
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: W1648607318