Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation.

ABSTRACT:

Background

The use of knowledge models facilitates information retrieval, knowledge base development, and therefore supports new knowledge discovery that ultimately enables decision support applications. Most existing works have employed machine learning techniques to construct a knowledge base. However, they often suffer from low precision in extracting entity and relationships. In this paper, we described a data-driven sublanguage pattern mining method that can be used to create a knowledge model. We combined natural language processing (NLP) and semantic network analysis in our model generation pipeline.

Methods

As a use case of our pipeline, we utilized data from an open source imaging case repository, Radiopaedia.org , to generate a knowledge model that represents the c

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC6035419 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature