title: [Structuralization of digestive endoscopy report based on NLP].
abstract: This paper presents a method based on NLP to realize structuralization of digestive endoscopy reports. The method is taking advantage of existing NLP's processing technologies and introducing minimal standard terminology (MST) to transform a narrative gastroscopy report into the structuralization report based on MST, whose accuracy rate is 92.3%.
authors.affiliation: Health Surveillance Office of Health Bureau, Center District, Jining, Shandong Province.
authors.forename: Xiao-feng
authors.initials: XF
authors.lastname: Kong
authors.forename: Ying
authors.initials: Y
authors.lastname: Li
authors.forename: Hao-min
authors.initials: HM
authors.lastname: Li
authors.forename: Xu-dong
authors.initials: XD
authors.lastname: Lu
mesh_terms: D016099:Endoscopy, Gastrointestinal / Q000379:methods*; D005568:Forms and Records Control; D016347:Medical Records Systems, Computerized; D009626:Terminology as Topic; D018875:Vocabulary, Controlled