Automatic information extraction for computerized clinical guideline.
Clinical Guidelines (CG) are recommendations on the appropriate treatment and care of people with specific diseases and conditions. CG should be used by both physicians and patients to make the informed decision. However, the CGs are not well used due to their complexity and because they are frequently updated. The computerized CGs are proposed to make use of the computer to do the decision making. However, it needs a lot of human effort to transform the narrative CG into computerized CG. In this paper, we proposed a method to use the NLP techniques to extract the fine-grained information from the text based CG automatically. Such information could be easily converted to the computer interpretable models.
IBM Research - China.
Huijia
H
Zhu
Yuan
Y
Ni
Peng
P
Cai
Feng
F
Cao
D000465:Algorithms; D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods; D017410:Practice Guidelines as Topic; D012660:Semantics; D009626:Terminology as Topic; D018875:Vocabulary, Controlled