Structuralization of digestive endoscopy report based on NLP
Kong, X-feng.; Li, Y.; Li, H-min.; Lu, X-dong.
Zhongguo Yi Liao Qi Xie Za Zhi 32(5): 348-351
2008
ISSN/ISBN: 1671-7104 PMID: 19119655 Document Number: 619379
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%.