Supporting the Abstraction of Clinical Practice Guidelines Using Information Extraction

Modelling clinical practice guidelines in a computer-interpretable format is a challenging and complex task. The modelling process involves both medical experts and computer scientists, who have to interact and communicate together. In order to support both modeller groups we propose to provide them with helpful information automatically generated using NLP methods. We identify this information using rules based on both syntactic and semantic information. The majority of the defined information extraction rules are based on semantic relationships derived from the UMLS Semantic Network. Findings in the evaluation indicate that using rules based on semantic and syntactic information provide valuable and helpful results.