| Abstract |
Relation extraction from medical text by using NLP tools has been considered to be one of the important topics in medical knowledge processing. Enhancing those NLP tools with the semantic processing by using some kinds of domain knowledge, such as medical ontologies, would improve the efficiency of medical knowledge extraction. In this talk, we will present an approach how to use the XMedLan NLP tool to obtain the semantic representation of medical knowledge with well-known medical ontologies such as UMLS and SNOMED CT. We will report two use cases of the semantic processing of medical knowledge. The first use case is how to semi-automatically use a rule-based formalization of eligibility criteria for clinical trials when processing clinical text. The second use case is how to convert unstructured knowledge in medical guidelines into structured ones, and how they can be used in searching for new and relevant evidences for evidence-based medical guideline updates. |