Format

Send to

Choose Destination
Stud Health Technol Inform. 2019 Aug 21;264:1263-1267. doi: 10.3233/SHTI190429.

SNOMEDtxt: Natural Language Generation from SNOMED Ontology.

Author information

1
Department of Biomedical Informatics, Columbia University, New York, NY, USA.

Abstract

SNOMED Clinical Terms (SNOMED CT) defines over 70,000 diseases, including many rare ones. Meanwhile, descriptions of rare conditions are missing from online educational resources. SNOMEDtxt converts ontological concept definitions and relations contained in SNOMED CT into narrative disease descriptions using Natural Language Generation techniques. Generated text is evaluated using both computational methods and clinician and lay user feedback. User evaluations indicate that lay people prefer generated text to the original SNOMED content, find it more informative, and understand it significantly better. This method promises to improve access to clinical knowledge for patients and the medical community and to assist in ontology auditing through natural language descriptions.

KEYWORDS:

Access to Information; Natural Language Processing; Systematized Nomenclature of Medicine

PMID:
31438128
DOI:
10.3233/SHTI190429
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for IOS Press
Loading ...
Support Center