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Phenotyping on EHR Data Using OWL and Semantic Web Technologies

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Book cover Smart Health (ICSH 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8040))

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Abstract

Objective: In this paper, we introduce our efforts on using semantic web technologies to execute phenotyping algorithms on Electronic Health Records (EHR) data.

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References

  1. GE/Intermountain Clinical Element Model Search, http://intermountainhealthcare.org/CEM/

  2. Rea, S., et al.: Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project. J. Biomed. Inform. 45, 763–771 (2012)

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Author information

Authors and Affiliations

  1. Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA

    Cui Tao, Dingcheng Li, Feichen Shen, Zonghui Lian, Jyotishman Pathak, Hongfang Liu & Christopher G. Chute

Authors
  1. Cui Tao
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  2. Dingcheng Li
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  3. Feichen Shen
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  4. Zonghui Lian
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  5. Jyotishman Pathak
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  6. Hongfang Liu
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  7. Christopher G. Chute
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Editor information

Editors and Affiliations

  1. MIS Department, The University of Arizona, Tucson, Arizona, U.S.A.

    Daniel Zeng

  2. Department of Information Science and Technology, Drexel University, USA

    Christopher C. Yang

  3. Dept. of Computer Science and Information Engineering, Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  4. Tsinghua University, Beijing, China

    Chunxiao Xing

  5. Department of Management Information Systems, University of Arizona, McClelland Hall 430, 1130 East Helen Street, 85721, Tucson, AZ, USA

    Hsinchun Chen

  6. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Fei-Yue Wang

  7. Chinese Academy of Sciences, Beijing, China

    Xiaolong Zheng

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© 2013 Springer-Verlag Berlin Heidelberg

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Tao, C. et al. (2013). Phenotyping on EHR Data Using OWL and Semantic Web Technologies. In: Zeng, D., et al. Smart Health. ICSH 2013. Lecture Notes in Computer Science, vol 8040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39844-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-39844-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39843-8

  • Online ISBN: 978-3-642-39844-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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