2008 International Conference on BioMedical Engineering and Informatics
Structuralization of Digestive Endoscopic Report Based on NLP
May 27-May 30
ISBN: 978-0-7695-3118-2
It is an inevitable transition from paper-based medical records to electronic medical records (EMR). EMR’s structuralization and standardization are important for efficient information retrieve and sharing. Presently, natural language processing (NLP) and structured data entry (SDE) are two different methods realizing EMR’s structuralizaion. Because SDE limits doctors’ free expression, this paper designs a system based on NLP and Minimal Standard Terminology (MST) that automatically maps digestive endoscopic narrative records to structured MST records and its accuracy is 92.3%.
Index Terms:
Structuralization, NLP, MST
Citation:
Ying Li, Junjie Li, Huilong Duan, Xudong Lu, "Structuralization of Digestive Endoscopic Report Based on NLP," bmei, vol. 1, pp.920-923, 2008 International Conference on BioMedical Engineering and Informatics, 2008