Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction

نویسندگان

  • Yaoyun Zhang
  • Ergin Soysal
  • Sungrim Moon
  • Jingqi Wang
  • Cui Tao
  • Hua Xu
چکیده

A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base.

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عنوان ژورنال:

دوره 2015  شماره 

صفحات  -

تاریخ انتشار 2015