Structuralization of Digestive Endoscopic Report Based on NLP
暂无分享,去创建一个
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%.
[1] William T. Hole,et al. Integration of a standard gastrointestinal endoscopy terminology in the UMLS Metathesaurus , 2002, AMIA.
[2] Ewan Klein,et al. Natural Language Processing with Python , 2009 .