Terminology Coverage from Semantic Annotated Health Documents.

Autor:	Ndangang M; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France., Grosjean J; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France., Lelong R; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France., Dahamna B; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France., Kergourlay I; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France., Griffon N; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France., Darmoni SJ; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France.
Jazyk:	angličtina
Zdroj:	Studies in health technology and informatics [Stud Health Technol Inform] 2018; Vol. 255, pp. 20-24.
Abstrakt:	Background: Unstructured health documents (e.g. discharge summaries) represent an important and unavoidable source of information. Methods: A semantic annotator identified all the concepts present in the health documents from the clinical data warehouse of the Rouen University Hospital. Results: 2,087,784,055 annotations were generated from a corpus of about 11.9 million documents with an average of 175 annotations per document. SNOMED CT, NCIt and MeSH were the top 3 terminologies that reported the most annotation. Discussion: As expected, the most general terminologies with the most translated concepts were those with the most concepts identified.
Databáze:	MEDLINE
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