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A Semantically-Enabled System for Inflammatory Bowel Diseases

  • Lei Xu
  • Zhisheng Huang
  • Hao Fan
  • Siwei Yu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10594)

Abstract

The incidence rate of Inflammatory Bowel Disease (IBD) in China is increasing in recent years and the cause of this disease is still not clear. In order to promote the development of this study, in this paper, we propose a Semantically-enabled System for Inflammatory Bowel Diseases (SeSIBD). It provides functions of semantic retrieval over patient data, statistical analysis and literature retrieval based on patient characteristics. SeSIBID is built on the top of LarKC, a semantic platform for scalable semantic data processing and reasoning. Although the current implementation of SeSIBID is a prototype system, it will provide an infrastructure for clinical decision making support for deep excavation and knowledge discovery on various of medical resources of IBD in the future.

Keywords

Inflammatory Bowel Diseases Crohn’s disease Semantic technology Semantic system 

Notes

Acknowledgments

This work was partially supported by a grant from the CSC (China Scholarship Council), the National Natural Science Foundation of China under grant number 71503189, the VU-China Cooperation fund, and the major cooperation project between mainland China and Taiwan under grant number 71661167007.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Information ManagementWuhan UniversityWuhanChina
  2. 2.Department of Computer ScienceVU University AmsterdamAmsterdamThe Netherlands

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