BmQGen: Biomedical query generator for knowledge discovery

Feichen Shen, Hongfang D Liu, Sunghwan Sohn, David Larson, Yugyung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

A large number of structured and unstructured data (e.g., EHRs, ontologies, reports) have been introduced by the biomedical community. Cross-domain data integration is identified as an important research problem for translational research. From an application perspective, identifying related concepts among medical ontologies is an important goal of life science research. It is essential to analyze how relations are specified to connect concepts in a single ontology or across multiple ontologies. With the explosion of cross domain datasets, it is extremely hard for researchers to discover knowledge from current infrastructures of ontologies. It is mainly a lack of the connectivity between the ontologies' cross domains and ontologies to unstructured data; even if they have specific biomedical knowledge in a more general and comprehensive level. Therefore, there is a need for a mechanism to do semantic partition and query generation for cross domain biomedical knowledge discovery. In this paper, we present such a model that clusters integrated data based on semantic closeness of predicates into different groups and produces meaningful queries to fully discover knowledge over a set of interlinked data sources. We have implemented a prototype of the BmQGen system and evaluated the proposed query model based on the predicate oriented clustering with colorectal surgical cohort from the Mayo Clinic.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1092-1097
Number of pages6
ISBN (Print)9781467367981
DOIs
StatePublished - Dec 16 2015
EventIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States
Duration: Nov 9 2015Nov 12 2015

Other

OtherIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
CountryUnited States
CityWashington
Period11/9/1511/12/15

Keywords

  • biomedical cross domain
  • knowledge discovery
  • query generation
  • semantic

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Health Informatics
  • Biomedical Engineering

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  • Cite this

    Shen, F., Liu, H. D., Sohn, S., Larson, D., & Lee, Y. (2015). BmQGen: Biomedical query generator for knowledge discovery. In Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 (pp. 1092-1097). [7359833] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2015.7359833