. Huang, Z., Yang, J., van Harmelen , F., & Hu, Q. Volume 10259 LNAI. Constructing disease-centric knowledge graphs: A case study for depression (short version), pages 48–52. Springer/Verlag, 2017.
doi  abstract   bibtex   
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.
@inbook{db25399349794a8f86dce8ed0ec8ac69,
  title     = "Constructing disease-centric knowledge graphs: A case study for depression (short version)",
  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.",
  author    = "Zhisheng Huang and Jie Yang and {van Harmelen}, Frank and Qing Hu",
  year      = "2017",
  doi       = "10.1007/978-3-319-59758-4_5",
  isbn      = "9783319597577",
  volume    = "10259 LNAI",
  series    = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  publisher = "Springer/Verlag",
  pages     = "48--52",
  booktitle = "Artificial Intelligence in Medicine - 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Proceedings",
}

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