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Constructing Disease-Centric Knowledge Graphs: A Case Study for Depression (short Version)

  • Zhisheng HuangEmail author
  • Jie Yang
  • Frank van Harmelen
  • Qing Hu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10259)

Abstract

In this paper we show how we used multiple large knowledge sources to construct a much smaller knowledge graph that is focussed on single disease (in our case major depression disorder). Such a disease-centric knowledge-graph makes it more convenient for doctors (in our case psychiatric doctors) to explore the relationship among various knowledge resources and to answer realistic clinical queries.

Keywords

Major Depressive Disorder Regular Expression Clinical Decision Support Knowledge Source Knowledge Resource 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work is partially supported by the Dutch national project COMMIT, the international cooperation project No. 61420106005 funded by National Natural Science Foundation of China, and the NWO-funded Project Re-Search. The fourth author is funded by the China Scholarship Council.

References

  1. 1.
    Ait-Mokhtar, S., Bruijn, B.D., Hagege, C., Rupi, P.: Intermediary-stage ie components, D3.5, Technical report, EURECA Project (2014)Google Scholar
  2. 2.
    Cyganiak, R., Wood, D., Lanthaler, M.: RDF 1.1 concepts and abstract syntax (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Zhisheng Huang
    • 1
    Email author
  • Jie Yang
    • 2
  • Frank van Harmelen
    • 1
  • Qing Hu
    • 1
    • 3
  1. 1.VU University AmsterdamAmsterdamThe Netherlands
  2. 2.Beijing Anding HospitalBeijingChina
  3. 3.College of Computer Science and TechnologyWuhan Univesity of Science and TechnologyWuhanChina

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