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A Scalable Clinical Intelligent Decision Support System

  • Conference paper
  • First Online:
Inclusive Smart Cities and Digital Health (ICOST 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9677))

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Abstract

It is a known fact that Clinical Decision Support System (CDSS) can help to improve the quality of medical. But the existing CDSSs are mostly focused on a typical disease. Single knowledge base and limited decision support results have a heavy impact on the application of CDSS in clinical medicine. To improve the scalability of extending new diseases to the CDSS, this paper proposes a scalable architecture named Open Clinical Decision Support Platform (OCDSP) that can customize and develop CDSS for any kind of diseases. Using the tool sets of OCDSP, one can configure medical knowledge bases, workflows of clinical paths, and clinic rules. Finally, a concrete CDSS of a specific disease can be customized from OCDSP. The software architecture of OCDSP is discussed detailed. In order to validate the scalability of OCDSP, the case study of how to customize CDSS for fracture and coronary heart disease is put forward.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (61202039) and the National High Technology Research and Development 863 Program of China (2012AA02A603).

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Correspondence to Qingshan Li .

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© 2016 Springer International Publishing Switzerland

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Chu, H., Yang, Y., Li, Q., Xu, Y., Wei, H. (2016). A Scalable Clinical Intelligent Decision Support System. In: Chang, C., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds) Inclusive Smart Cities and Digital Health. ICOST 2016. Lecture Notes in Computer Science(), vol 9677. Springer, Cham. https://doi.org/10.1007/978-3-319-39601-9_14

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  • DOI: https://doi.org/10.1007/978-3-319-39601-9_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39600-2

  • Online ISBN: 978-3-319-39601-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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