[Structuralization of digestive endoscopy report based on NLP].
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%.
Kong
Xiao-feng
XF
Health Surveillance Office of Health Bureau, Center District, Jining, Shandong Province.
Li
Ying
Y
Li
Hao-min
HM
Lu
Xu-dong
XD
D016099:Endoscopy, Gastrointestinal / Q000379:methods*; D005568:Forms and Records Control; D016347:Medical Records Systems, Computerized; D009626:Terminology as Topic; D018875:Vocabulary, Controlled