Constructing disease-centric knowledge graphs: A case study for depression (short version)

Zhisheng Huang; Jie Yang; Frank van Harmelen; Qing Hu

doi:10.1007/978-3-319-59758-4_5

Constructing disease-centric knowledge graphs: A case study for depression (short version)

Zhisheng Huang^*, Jie Yang, Frank van Harmelen, Qing Hu

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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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.

Original language	English
Title of host publication	Artificial Intelligence in Medicine
Subtitle of host publication	16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings
Editors	Annette ten Teije, Christian Popow, John H. Holmes, Lucia Sacchi
Publisher	Springer/Verlag
Pages	48-52
Number of pages	5
ISBN (Electronic)	9783319597584
ISBN (Print)	9783319597577
DOIs	https://doi.org/10.1007/978-3-319-59758-4_5
Publication status	Published - 2017
Event	16th Conference on Artificial Intelligence in Medicine, AIME 2017 - Vienna, Austria Duration: 21 Jun 2017 → 24 Jun 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10259 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th Conference on Artificial Intelligence in Medicine, AIME 2017
Country/Territory	Austria
City	Vienna
Period	21/06/17 → 24/06/17

Funding

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.

Funders	Funder number
Dutch national project COMMIT	61420106005
NWO-funded
National Natural Science Foundation of China
China Scholarship Council

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-319-59758-4_5

Constructing Disease-Centric Knowledge GraphsFinal published version, 386 KBLicence: Article 25fa Dutch Copyright Act

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Huang, Z., Yang, J., van Harmelen, F., & Hu, Q. (2017). Constructing disease-centric knowledge graphs: A case study for depression (short version). In A. ten Teije, C. Popow, J. H. Holmes, & L. Sacchi (Eds.), Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings (pp. 48-52). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10259 LNAI). Springer/Verlag. https://doi.org/10.1007/978-3-319-59758-4_5

Huang, Zhisheng ; Yang, Jie ; van Harmelen, Frank et al. / Constructing disease-centric knowledge graphs : A case study for depression (short version). Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings. editor / Annette ten Teije ; Christian Popow ; John H. Holmes ; Lucia Sacchi. Springer/Verlag, 2017. pp. 48-52 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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",

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doi = "10.1007/978-3-319-59758-4_5",

language = "English",

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Huang, Z, Yang, J, van Harmelen, F & Hu, Q 2017, Constructing disease-centric knowledge graphs: A case study for depression (short version). in A ten Teije, C Popow, JH Holmes & L Sacchi (eds), Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10259 LNAI, Springer/Verlag, pp. 48-52, 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, 21/06/17. https://doi.org/10.1007/978-3-319-59758-4_5

Constructing disease-centric knowledge graphs: A case study for depression (short version). / Huang, Zhisheng; Yang, Jie; van Harmelen, Frank et al.
Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings. ed. / Annette ten Teije; Christian Popow; John H. Holmes; Lucia Sacchi. Springer/Verlag, 2017. p. 48-52 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10259 LNAI).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AB - 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.

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Huang Z, Yang J, van Harmelen F, Hu Q. Constructing disease-centric knowledge graphs: A case study for depression (short version). In ten Teije A, Popow C, Holmes JH, Sacchi L, editors, Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings. Springer/Verlag. 2017. p. 48-52. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2017 May 30. doi: 10.1007/978-3-319-59758-4_5

Constructing disease-centric knowledge graphs: A case study for depression (short version)

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